A Distributed Communication Integration Verification Method for Smart Home

Abstract

The present invention discloses a distributed communication integration verification method for smart home, which specifically relates to the field of smart home, including S1: monitoring and collecting corresponding signals of smart home, S2: locating interference sources, S3: intelligently suppressing interference sources, S4: adapting and extending communication protocols, S5: analyzing distributed data, S6: evaluating and monitoring the performance of smart home, and S7: optimizing the organizational structure of smart home. A distributed communication integration verification method for smart home precisely locates the positions of interference sources that cause signal interference when multiple smart devices are running simultaneously through signal positioning operations, effectively solving the problem of communication interruption between devices caused by signal interference; verifies the communication between smart home devices by establishing a protocol compatibility matrix to ensure effective communication between devices with different protocols; and guarantees efficient communication and data processing in the case of large-scale device networking through distributed processing based on the first signal integration information.

Description

Technical Field

[0001] The present invention relates to the technical field of smart home, and more specifically, the present invention relates to a distributed communication integration verification method for smart home. Background Art

[0002] With the rapid development of artificial intelligence and Internet of Things technologies, various smart devices have continuously flooded into family life, from smart door locks, smart lighting systems to smart home appliances, etc., which are interconnected through different communication methods and use machine learning for intelligent analysis, including positioning, prediction and scheduling, etc., so as to realize intelligent life scenarios such as home security defense, special care for the elderly and children, and home environment management.

[0003] The smart home system stores and analyzes the massive data generated and collected by the home Internet of Things in real time in the cloud and edge, and performs intelligent analysis on the data through machine learning to ensure that information can be accurately exchanged between smart devices, so that the instructions issued by users can be quickly and accurately executed, thereby intelligently controlling and managing home energy and reducing waste.

[0004] However, in actual use, there are still some drawbacks, such as signal interference generated when multiple smart devices run simultaneously, resulting in communication interruption and data transmission delay between devices; there is a lag in seamless communication integration verification between new and old devices and different protocols; in the face of large-scale device networking communication, there is a lack of sufficient scalability and it is difficult to meet the needs of users for continuously increasing the number of smart devices. Summary of the Invention

[0005] In order to overcome the above-mentioned defects of the prior art, the present invention provides a distributed communication integration verification method and system for smart home, through the following solutions to solve the problems raised in the above background art.

[0006] To achieve the above object, the present invention provides the following technical solutions:

[0007] A distributed communication integration verification method for smart home, characterized by comprising:

[0008] S1: Monitor and collect corresponding signals of smart home: Real-time monitor the signal status of smart devices when running in the smart home environment, and collect the smart devices that send and receive to obtain the first communication signal;

[0009] S2: Locate the interference source: Perform signal location operation on the signal anomaly of the first communication signal, and the signal location operation is used to obtain the second communication signal;

[0010] S3: Intelligent interference source suppression: Obtain the intelligent anti-interference model, and based on the intelligent anti-interference model, obtain the second signal integration information corresponding to the second communication signal through the second communication signal in the interference source positioning module;

[0011] S4: Adapt and expand the communication protocol: Identify the device protocol corresponding to the first communication signal, and optimize and adjust the protocol based on the second signal integration information corresponding to the second communication signal to obtain the first signal integration information;

[0012] S5: Analyze distributed data: Perform distributed processing on the first signal integration information, and based on the overall architecture and operation requirements of the smart home, obtain the third communication signal;

[0013] S6: Evaluate and monitor the performance of the smart home: Obtain the intelligent performance evaluation model, and based on the intelligent performance evaluation model, obtain the third signal integration information corresponding to the third communication signal through the third communication signal in the distributed data processing module;

[0014] S7: Optimize the organizational structure of the smart home: Perform dynamic verification based on the third signal integration information to verify and optimize the performance of the smart home architecture.

[0015] Preferably, for S2, obtaining the second communication signal specifically includes:

[0016] Perform signal positioning operations according to the abnormal type corresponding to the abnormal feature, the layout characteristics and distribution of smart home devices. The signal positioning operations include time difference of arrival (TDOA) positioning, received signal strength indication (RSSI) positioning, and angle of arrival (AOA) positioning;

[0017] Determine the configuration parameters in the positioning technology. The configuration parameters include the position coordinates of each monitoring point, the propagation speed of the communication signal, and the conversion parameter between the signal strength and the distance from the monitoring point.

[0018] Preferably, for S2, obtaining the second communication signal specifically includes:

[0019] Perform signal positioning operations based on time difference of arrival (TDOA) positioning. According to the signal anomaly situation corresponding to the first communication signal, that is, the abnormal type corresponding to the abnormal feature, extract the communication signal transmission timestamps when the communication signal arrives at each monitoring point. Based on the transmission time t of the communication signal from monitoring point n to monitoring point m m and the transmission time t of the communication signal from monitoring point m to monitoring point n n , calculate the time difference of arrival Δt of the signal between monitoring point n and monitoring point m mn , specifically expressed as:

[0020] Δt mn =|t m -t n|,

[0021] wherein, n and m represent the indices of different monitoring points, |t m -t n | represents the absolute value of the time difference of signal arrival;

[0022] Based on the position coordinates n(x n , y n , z n ) of monitoring point n, the position coordinates m(x m , y m , z m ) of monitoring point m, the communication signal propagation speed v, and the time difference of signal arrival Δt mn between monitoring point n and monitoring point m, the interference source coordinate objective function F(IS(X, Y, Z)) is obtained, which is specifically expressed as:

[0023] F(IS(X, Y, Z)) = F mpn 2 (m, n) + F mpn-1 2 (m, n) + … + F 1 2 (m, n),

[0024] wherein, mpn represents the total number of interference source estimation functions, and the value of mpn is C pn 2 , pn represents the total number of monitoring points, that is, the combination number of taking 2 monitoring points from the total number pn of monitoring points, and F(m, n) represents the interference source estimation function between monitoring point n and monitoring point m, which is specifically expressed as:

[0025] ,

[0026] wherein, X, Y, and Z respectively represent the coordinate positions of the interference source IS.

[0027] Preferably, in step S3, obtaining the second signal integration information specifically includes:

[0028] Performing matching analysis on the second communication signal to obtain the interference source characteristics corresponding to the second communication signal, and the interference source characteristics are the target key characteristics corresponding to the interference source in the second communication signal, and the target key characteristics include the interference source type, interference intensity, interference source coordinates, and the device identifier to which the interference source belongs;

[0029] In the preset communication integration database, obtaining the intelligent anti-interference model corresponding to the interference source characteristics, and the preset communication integration database is used to store the corresponding relationship between the interference source characteristics and the intelligent anti-interference model.

[0030] Preferably, in step S4, obtaining the first signal integration information specifically includes:

[0031] Establish a protocol compatibility matrix based on the obtained device protocol type and version number. The protocol compatibility matrix is a compatibility relationship based on a large number of experimental tests and the specific protocols and versions adopted by the current devices.

[0032] Verify the communication between smart home devices through the protocol compatibility matrix.

[0033] Perform a protocol optimization and adjustment strategy based on the second signal integration information. The protocol optimization and adjustment strategy includes standardizing the protocol format, modifying the protocol data format, conversion rules, adjusting communication parameters, and replacing protocol conversion plugins.

[0034] In a preset communication integration database, obtain the protocol optimization and adjustment strategy corresponding to the protocol compatibility matrix. The preset communication integration database is used to store the corresponding relationship between the protocol compatibility matrix and the protocol optimization and adjustment strategy.

[0035] Preferably, in step S5, obtaining the third communication signal specifically includes:

[0036] Perform distributed processing based on the first signal integration information. The distributed processing includes data partition analysis, parallel processing analysis, and load balancing analysis.

[0037] Integrate according to the first signal integration information corresponding to the distributed processing to obtain the third communication signal.

[0038] Preferably, in step S5, obtaining the third communication signal specifically includes:

[0039] Perform distributed processing using data partitioning, perform classification operations according to the first signal integration information to obtain the allocation rules corresponding to the first signal integration information. The allocation rules are the target processing partitions corresponding to the first signal integration information. The target processing partitions include device control instructions, device status feedback data, and multimedia data.

[0040] Perform distributed processing using parallel processing. According to the first signal integration information, decompose the device communication stability verification task into multiple subtasks and verify different groups of smart home devices.

[0041] Decompose the data transmission efficiency calculation task into multiple subtasks, and each subtask is responsible for calculating the data transmission efficiency between specific devices.

[0042] Summarize the analysis results of the subtasks.

[0043] Distributed processing is carried out using load balancing, and the load conditions of each processing node are continuously monitored and analyzed. The load conditions include the current processing task volume, available resources, and network bandwidth occupancy of the processing node;

[0044] Based on the load monitoring results and the first signal integration information, an allocation operation is performed. The allocation operation is determined based on the remaining available resources, current processing task volume, and network bandwidth of the processing node.

[0045] Preferably, in step S6, obtaining the third signal integration information corresponding to the third communication signal specifically includes:

[0046] According to the third communication signal, the performance indicators corresponding to the third communication signal are calculated through an intelligent performance evaluation model. The performance indicators include the device connection success rate, data transmission rate, and average response time. The actual calculated values of the performance indicators are compared and analyzed with the preset standard values;

[0047] Comprehensively evaluate the mutual relationship between multiple performance indicators;

[0048] Regularly receive the third communication signal, calculate the performance indicators corresponding to the third communication signal through the intelligent performance evaluation model to obtain the change situation of the performance indicators, so as to obtain the third signal integration information.

[0049] To achieve the above object, the present invention provides the following technical solution: A distributed communication integration verification system for smart home, including a system operation database, a system central processing module, and a user information terminal. Implementing the above-mentioned distributed communication integration verification method for smart home includes:

[0050] Signal monitoring and acquisition module: used to monitor the signal status during the operation of smart devices in the smart home environment in real time, and collect the smart devices that send and receive to obtain the first communication signal;

[0051] Interference source location module: used to perform signal location operations on the signal anomaly situation corresponding to the first communication signal in the signal monitoring and acquisition module. The signal location operation is used to obtain the second communication signal;

[0052] Intelligent interference suppression module: used to obtain an intelligent anti-interference model, and according to the intelligent anti-interference model, obtain the second signal integration information corresponding to the second communication signal through the second communication signal in the interference source location module;

[0053] Protocol adaptation and extension module: used to identify the device protocol corresponding to the first communication signal in the signal monitoring and acquisition module, and optimize and adjust the protocol based on the second signal integration information corresponding to the second communication signal in the intelligent interference suppression module to obtain the first signal integration information;

[0054] Distributed Data Processing Module: It is used to perform distributed processing on the first signal integration information in the protocol adaptation and extension module, and obtain the third communication signal based on the overall architecture and operation requirements of the smart home.

[0055] Smart Home Performance Monitoring Module: It is used to obtain the intelligent performance evaluation model, and obtain the third signal integration information corresponding to the third communication signal according to the intelligent performance evaluation model through the third communication signal in the distributed data processing module.

[0056] Organization Structure Optimization Module: It is used to perform dynamic verification based on the third signal integration information in the smart home performance monitoring module to verify and optimize the performance of the smart home architecture.

[0057] The system operation database includes all data texts of the smart home distributed communication integration verification system, and real-time collects the information texts output by each module. The system central processing module is used to control the information text instructions output by each module in the control method, and the user information terminal is an information output device for receiving the smart home distributed communication integration verification system.

[0058] Technical Effects and Advantages of the Invention:

[0059] By using signal positioning operations, the present invention accurately locates the position of the interference source of signal interference generated when multiple smart devices are running simultaneously, effectively solving the problem of communication interruption between devices caused by signal interference.

[0060] By establishing a protocol compatibility matrix to verify the communication between smart home devices and optimizing the adjustment strategy to obtain the first signal integration information, the present invention ensures effective communication between devices with different protocols.

[0061] By performing distributed processing based on the first signal integration information, the present invention meets the needs of users to continuously increase the number of smart devices, ensuring efficient communication and data processing in the case of large-scale device networking. Brief Description of the Drawings

[0062] Figure 1 It is a method step diagram of the present invention.

[0063] Figure 2 It is a method flow chart of the present invention.

[0064] Figure 3 It is a method structure schematic diagram of the present invention.

[0065] Description of the Reference Numerals: 300, a schematic diagram of the system processing structure corresponding to a distributed communication integration verification method for smart home; 301, system central processor; 302, communication bus; 303, system database; 304, user information terminal. Detailed Embodiments

[0066] Next, in combination with the accompanying drawings in the embodiments of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0067] The terms used in the following embodiments of this application are only for the purpose of describing specific embodiments and are not intended to limit this application. As used in the specification of this application, the singular forms "a", "an", "the", "above-mentioned", "the foregoing", "this" are also intended to include the plural forms, unless the context clearly indicates otherwise. It should also be understood that the term "and / or" used in this application refers to and includes any or all possible combinations of one or more of the listed items.

[0068] Hereinafter, the terms "first", "second", and "third" are only used for descriptive purposes and cannot be understood as implying or suggesting relative importance or implicitly indicating the quantity of the indicated technical features. Thus, the features defined with "first", "second", and "third" may explicitly or implicitly include one or more of such features. In the description of the embodiments of this application, unless otherwise stated, the meaning of "a plurality" is two or more.

[0069] As shown in the attached Figure 1 A distributed communication integration verification method for a smart home, including S1: monitoring and collecting corresponding signals of the smart home, S2: locating interference sources, S3: intelligently suppressing interference sources, S4: adapting and expanding communication protocols, S5: analyzing distributed data, S6: evaluating and monitoring the performance of the smart home, and S7: optimizing the organizational structure of the smart home.

[0070] S1: Monitoring and collecting corresponding signals of the smart home: Real-time monitoring of the signal status of smart devices during operation in the smart home environment, and collecting the smart devices that send and receive to obtain the first communication signal.

[0071] Specifically, the smart home distributed communication integration verification system deploys key monitoring points based on the layout characteristics and distribution of smart home devices. The key monitoring points are equipped with corresponding monitoring devices, and the monitoring devices include but are not limited to signal monitors, smart gateways, etc.; through the initialization operation of the monitoring devices set at the key monitoring points, the initialization operation includes but is not limited to setting the monitoring frequency range, setting the sampling interval, specifying the data storage format, etc., to monitor the signal status during the operation of smart devices in the smart home environment in real time, and obtain the first communication signal. The first communication signal includes the communication signal strength of each smart home device, the communication signal frequency of each smart home device, the communication signal waveform of each smart home device, the identification of each smart home device, and the communication signal transmission timestamp of each smart home device.

[0072] In a possible implementation manner, obtaining the first communication signal includes: real-time monitoring of the operating status of smart home devices in the smart home environment through the initialized monitoring devices, classifying and sorting the original data collected by the monitoring devices according to three dimensions of device, time, and signal characteristics to form a structured data format; obtaining the first communication signal and storing it in a preset integration verification database, and comparing it with a large amount of historical data to preliminarily judge the abnormal situation of the original data collected in real time.

[0073] Specifically, if it is preliminarily judged that there is an abnormal situation in the first communication signal collected and sorted in real time, then step S2 is implemented to perform a signal positioning operation on the signal abnormal situation corresponding to the first communication signal; if it is preliminarily judged that there is no abnormal situation in the first communication signal collected and sorted in real time, then step S4 is directly implemented to identify the device protocol corresponding to the first communication signal, and optimize and adjust the protocol based on the second signal integration information corresponding to the second communication signal to obtain the first signal integration information.

[0074] In this embodiment, when a smart home device communicates with another smart home device, if the signal strength suddenly drops significantly, it is determined that there is an interference factor between the two, resulting in an increase in signal attenuation.

[0075] S2: Locate the interference source: Perform a signal positioning operation on the signal abnormal situation corresponding to the first communication signal. The signal positioning operation is used to obtain the second communication signal.

[0076] Specifically, when the smart home distributed communication integration verification system preliminarily judges that there is an abnormal situation in the first communication signal collected and sorted in real time, through the signal positioning operation, the second communication signal is obtained. The second communication signal includes the coordinate position of the interference source, the identification of the smart device corresponding to the interference source, and the abnormal type of the interference source.

[0077] In a possible implementation, obtaining the second communication signal includes: receiving abnormal signal data in the original data format corresponding to the first communication signal, and identifying and extracting the abnormal characteristics corresponding to the abnormal signal data by using the cyclic redundancy check (CRC) algorithm; classifying and sorting the abnormal characteristics to obtain the abnormal type corresponding to the abnormal characteristics, where the abnormal type is the signal abnormal condition corresponding to the first communication signal, and the signal abnormal condition includes a sudden drop in abnormal intensity, abnormal frequency drift, abnormal waveform distortion, abnormal intelligent device identifier, and the time when the abnormal condition occurs.

[0078] In a possible implementation, obtaining the second communication signal further includes: performing signal positioning operations according to the abnormal type corresponding to the abnormal characteristics, the layout characteristics, and the distribution of smart home devices. The signal positioning operations include time difference of arrival (TDOA) positioning, received signal strength indication (RSSI) positioning, and angle of arrival (AOA) positioning; determining the configuration parameters in the positioning technology, where the configuration parameters include the position coordinates of each monitoring point, the propagation speed of the communication signal, and the conversion parameter between the signal strength and the distance from the monitoring point.

[0079] In this embodiment, for the signal abnormal condition corresponding to the first communication signal, that is, the abnormal type corresponding to the abnormal characteristics, when the time information of the signal arriving at different monitoring points is obtained and it is required to locate a specific smart device, TDOA positioning is selected for signal positioning operations.

[0080] In this embodiment, when performing signal positioning operations through RSSI positioning, the conversion parameter SSD between the determined signal strength and the distance is specifically expressed as:

[0081] SSD = A - (10 × n × log 10 d) + ND,

[0082] where A represents the communication signal strength when d = 1 m, n represents the path loss exponent, and its value range is (2, 6), d represents the distance from the monitoring point, and ND represents the smart home environment impact factor with an average value of 0.

[0083] Specifically, when performing signal positioning operations through TDOA positioning, according to the signal abnormal condition corresponding to the first communication signal, that is, the abnormal type corresponding to the abnormal characteristics, the communication signal transmission timestamps of the communication signal arriving at each monitoring point are extracted. Based on the transmission time t m of the communication signal from monitoring point n to monitoring point m and the transmission time t n of the communication signal from monitoring point m to monitoring point n, the time difference of arrival Δt between monitoring point n and monitoring point m is calculated mn , and it is specifically expressed as:

[0084] Δt mn = |t m - tn |,

[0085] where n and m represent the indices of different monitoring points, and |t m -t n | represents the absolute value of the time difference of arrival of the signal;

[0086] Based on the position coordinates n(x n , y n , z n ) of the monitoring point n, the position coordinates m(x m , y m , z m ) of the monitoring point m, the communication signal propagation speed v, and the time difference of arrival Δt of the signal between the monitoring point n and the monitoring point m mn , the interference source coordinate objective function F(IS(X, Y, Z)) is obtained, which is specifically expressed as:

[0087] F(IS(X, Y, Z)) = F mpn 2 (m, n) + F mpn-1 2 (m, n) +... + F 1 2 (m, n),

[0088] where mpn represents the total number of interference source estimation functions, and the value of mpn is C pn 2 , pn represents the total number of monitoring points, that is, the combination number of taking 2 monitoring points from the total number pn of monitoring points, and F(m, n) represents the interference source estimation function between the monitoring point n and the monitoring point m, which is specifically expressed as:

[0089] ,

[0090] where X, Y, and Z respectively represent the coordinate positions of the interference source IS.

[0091] In this embodiment, the coordinate positions of multiple interference sources IS are obtained through multiple interference source estimation functions and interference source coordinate objective functions combined in pairs. If the solved position coordinates are inside the wall and do not conform to the actual situation, they are excluded, and the interference source position coordinates that conform to the actual situation are screened out.

[0092] S3: Intelligent interference source suppression: Obtain the intelligent anti-interference model, and according to the intelligent anti-interference model, obtain the second signal integration information corresponding to the second communication signal through the second communication signal in the interference source positioning module.

[0093] Specifically, the intelligent anti-interference model is a pre-constructed learning model. By inputting the second communication signal into the intelligent anti-interference model, the intelligent anti-interference model obtains the second signal integration information according to the second communication signal. The second signal integration information includes the actual interference intensity after suppression, the communication recovery situation of the affected device after the implementation of the suppression measures, and the impact on the communication of other surrounding intelligent devices.

[0094] In a possible implementation manner, obtaining the second signal integration information includes: comprehensively establishing an intelligent anti-interference model based on a large amount of historical data stored in a preset integration verification database and analysis reports of interference cases. The intelligent anti-interference model is pre-initialized and trained through the behavior characteristics of different types of interference sources in various smart home scenarios, the influence rules on communication devices and links, and the effective suppression strategies to be adopted for different interference situations.

[0095] In a possible implementation manner, obtaining the second signal integration information further includes: performing matching analysis on the second communication signal to obtain the interference source characteristics corresponding to the second communication signal. The interference source characteristics are the target key characteristics corresponding to the interference source in the second communication signal, and the target key characteristics include the interference source type, interference intensity, interference source coordinates, and the device identifier to which the interference source belongs; in the preset communication integration database, obtain the intelligent anti-interference model corresponding to the interference source characteristics. The preset communication integration database is used to store the correspondence between the interference source characteristics and the intelligent anti-interference model.

[0096] In this embodiment, when the interference source is of the same frequency and high intensity, the intelligent anti-interference model selects to adjust the communication frequency of the interfered device to a relatively idle frequency band; when the interference source is strong at close range, the intelligent anti-interference model selects to reduce the transmission power of the interference source; when the interference source is caused by a malfunction of an intelligent device, the intelligent anti-interference model selects to perform restart, software update, or hardware maintenance measures on the device.

[0097] In a possible implementation manner, obtaining the second signal integration information further includes: based on the interference source characteristic matching analysis result, obtaining multiple preset interference suppression strategies. The multiple preset interference suppression strategies include target interference source characteristics, and the target interference source characteristics are any one of the interference suppression strategies in the multiple preset interference suppression strategies; determining and optimizing the interference suppression parameters; generating an interference suppression instruction based on the interference suppression strategy and the interference suppression parameters. The interference suppression instruction is the interference suppression execution measure for the smart home device corresponding to the specified device identifier; re-monitoring the signal status of the interference source corresponding to the second communication signal and the affected smart home to obtain the second signal integration information.

[0098] Specifically, the adjustment of the preset interference suppression strategy corresponding to the interference suppression parameters includes: when the communication frequency of the device needs to be adjusted, determining the specific target frequency value based on the communication frequency usage of smart home devices in the smart home environment and the currently available idle frequency bands; when the transmission power of the interference source needs to be reduced, optimizing the power reduction amplitude.

[0099] S4: Adapt and extend the communication protocol: Identify the device protocol corresponding to the first communication signal, and optimize and adjust the protocol based on the second signal integration information corresponding to the second communication signal to obtain the first signal integration information.

[0100] In a possible implementation manner, obtaining the first signal integration information includes: performing a parsing operation on the first communication signal corresponding to the preliminary judgment of no abnormal situation in S1 and the second signal integration information corresponding to the second communication signal to obtain the device protocol type and version number corresponding to the smart device identifier in the first communication signal.

[0101] In a possible implementation manner, obtaining the first signal integration information further includes: establishing a protocol compatibility matrix according to the obtained device protocol type and version number, where the protocol compatibility matrix is the compatibility relationship based on a large number of experimental tests and the specific protocols and versions adopted by the current devices; verifying the communication between smart home devices through the protocol compatibility matrix;

[0102] In this embodiment, device A uses Wi-Fi protocol version A1, and device B uses Bluetooth protocol version B1. If it is obtained through the protocol compatibility matrix that the two protocols and versions are incompatible, then perform protocol adaptation operations;

[0103] According to the second signal integration information, perform a protocol optimization and adjustment strategy, where the protocol optimization and adjustment strategy includes standardizing the protocol format, modifying the protocol data format, conversion rules, adjusting communication parameters, and replacing protocol conversion plugins; in the preset communication integration database, obtain the protocol optimization and adjustment strategy corresponding to the protocol compatibility matrix, and the preset communication integration database is used to save the corresponding relationship between the protocol compatibility matrix and the protocol optimization and adjustment strategy.

[0104] In this embodiment, if the protocol optimization and adjustment strategy needs to perform data format conversion on two incompatible protocols, then find the specific conversion rules and adaptation plugins for the two protocols respectively in the preset communication integration database.

[0105] S5: Analyze distributed data: Perform distributed processing on the first signal integration information, and based on the overall architecture and operation requirements of the smart home, to obtain the third communication signal.

[0106] In a possible implementation manner, obtaining the third communication signal includes: performing distributed processing based on the first signal integration information, where the distributed processing includes data partitioning analysis, parallel processing analysis, and load balancing analysis;

[0107] In this embodiment, in a large-scale smart home environment with significant differences in the communication data types of different smart home devices, data partitioning is implemented to divide different types of communication data into different processors for analysis and processing;

[0108] In this embodiment, when the user needs to perform real-time control of smart home devices, parallel processing is selected to enable multiple processors to analyze and process communication data simultaneously;

[0109] In this embodiment, if the hardware devices for network communication are not updated and communication is prone to congestion, load balancing is adopted to distribute the communication data traffic to different processing nodes to ensure that the workload of each node is relatively balanced;

[0110] It should be noted that when using data partitioning for distributed processing, classification operations are performed according to the first signal integration information to obtain the allocation rules corresponding to the first signal integration information. The allocation rules are the target processing partitions corresponding to the first signal integration information, and the target processing partitions include device control instructions, device status feedback data, and multimedia data;

[0111] It should be noted that when using parallel processing for distributed processing, according to the first signal integration information, the device communication stability verification task is decomposed into multiple subtasks for verification for different groups of smart home devices; the data transmission efficiency calculation task is decomposed into multiple subtasks, and each subtask is responsible for calculating the data transmission efficiency between specific device pairs; the analysis results of the subtasks are summarized;

[0112] It should be noted that when using load balancing for distributed processing, the load conditions of each processing node are continuously monitored and analyzed. The load conditions include the current processing task volume, available resources, and network bandwidth occupancy of the processing node; allocation operations are performed based on the load monitoring results and the first signal integration information, and the allocation operations are determined based on the remaining available resources, current processing task volume, and network bandwidth of the processing node;

[0113] Specifically, integration is performed according to the first signal integration information corresponding to the distributed processing to obtain the third communication signal. The third communication signal includes the packet loss rate reduction rate, connection success rate improvement rate, data transmission efficiency, optimized data format, and data allocation in the system.

[0114] S6: Evaluate and monitor the performance of the smart home: Obtain the smart performance evaluation model, and obtain the third signal integration information corresponding to the third communication signal according to the smart performance evaluation model through the third communication signal.

[0115] Specifically, the intelligent performance evaluation model is a pre-constructed learning model. By inputting the third communication signal into the intelligent performance evaluation model, the intelligent performance evaluation model obtains the third signal integration information based on the third communication signal.

[0116] In a possible implementation manner, obtaining the third signal integration information corresponding to the third communication signal includes: according to the third communication signal, calculating the performance indicators corresponding to the third communication signal through the intelligent performance evaluation model. The performance indicators include the device connection success rate, data transmission rate, and average response time. Comparing and analyzing the actual calculated values of the performance indicators with the preset standard values;

[0117] In this embodiment, if the actually calculated device connection success rate index is higher than the lowest acceptable success rate, it indicates that the device connection performance is good;

[0118] Comprehensively evaluate the mutual relationship between multiple performance indicators;

[0119] In this embodiment, the evaluation results of each performance indicator are integrated through weighted average to obtain a comprehensive evaluation of the overall performance of the smart home system, so as to judge whether the system meets the overall operation requirements of users;

[0120] Regularly receive the third communication signal, calculate the performance indicators corresponding to the third communication signal through the intelligent performance evaluation model to obtain the change situation of the performance indicators, so as to obtain the third signal integration information. The third signal integration information includes the actual values of each performance indicator, standard comparison data, comprehensive evaluation results, and the change trend of the performance indicators.

[0121] S7: Optimize the smart home organizational structure: Perform dynamic verification based on the third signal integration information to verify and optimize the performance of the smart home architecture.

[0122] Specifically, based on the third signal integration information, set dynamic verification indicators. The dynamic verification indicators include the connection status of the device, data transmission process, instruction response situation, and device energy consumption;

[0123] In this embodiment, by continuously tracking whether the device connection success rate always remains above the set threshold, the stability of the device connection is verified; observing whether the data transmission rate meets the high-efficiency requirements under different load conditions to verify the performance of data transmission; checking the change situation of the system response time and other performance indicators when new devices are connected to verify the scalability of the system, etc.;

[0124] According to the dynamic verification results, analyze the performance bottlenecks and problem areas corresponding to the smart home environment and take optimization measures to readjust the first signal integration information;

[0125] Specifically, adjust the placement position of the device to improve signal coverage, update the device driver or firmware to enhance compatibility to ensure stable device connection; adopt a mesh topology instead of a star topology to ensure smooth data transmission; upgrade the transmission protocol; adjust the networking architecture, increase the number of device access points, and optimize the access point settings to dynamically adjust the scalability of the smart home;

[0126] In this embodiment, when the device connection success rate is lower than the set threshold in area A, there are unstable connection factors; when the data transmission rate cannot meet the high-efficiency requirements in a large data transmission scenario, it belongs to an unreasonable network topology structure; when the response time increases significantly when a new device is accessed and other performance indicators decline significantly, there are scalability defect problems.

[0127] As shown in the attached Figure 2 A distributed communication integration verification system for a smart home, including a system operation database, a system central processing module, and a user information terminal, further including: a signal monitoring and acquisition module, an interference source location module, an intelligent interference suppression module, a protocol adaptation and extension module, a distributed data processing module, a smart home performance monitoring module, and an organizational structure optimization module.

[0128] The signal monitoring and acquisition module: is used to monitor the signal status during the operation of smart devices in the smart home environment in real time, and collect the smart devices that send and receive to obtain the first communication signal;

[0129] The interference source location module: is used to perform signal location operations on the signal anomaly situations corresponding to the first communication signal in the signal monitoring and acquisition module, and the signal location operation is used to obtain the second communication signal;

[0130] The intelligent interference suppression module: is used to obtain an intelligent anti-interference model, and based on the intelligent anti-interference model, through the second communication signal in the interference source location module, obtain the second signal integration information corresponding to the second communication signal;

[0131] The protocol adaptation and extension module: is used to identify the device protocol corresponding to the first communication signal in the signal monitoring and acquisition module, and optimize and adjust the protocol based on the second signal integration information corresponding to the second communication signal in the intelligent interference suppression module to obtain the first signal integration information;

[0132] The distributed data processing module: is used to perform distributed processing on the first signal integration information in the protocol adaptation and extension module, and based on the overall architecture and operation requirements of the smart home, to obtain the third communication signal;

[0133] Smart Home Performance Monitoring Module: It is used to obtain an intelligent performance evaluation model and, based on the intelligent performance evaluation model, obtain the third signal integration information corresponding to the third communication signal through the third communication signal in the distributed data processing module;

[0134] Organization Structure Optimization Module: It is used to perform dynamic verification based on the third signal integration information in the Smart Home Performance Monitoring Module to verify and optimize the performance of the smart home architecture;

[0135] The system operation database includes all data texts of the smart home distributed communication integration verification system and collects the information texts output by each module in real time. The system central processing module is used to control the information text instructions output by each module in the control method, and the user information terminal is an information output device for receiving the smart home distributed communication integration verification system.

[0136] Secondly: In the attached drawings of the disclosed embodiments of the present invention, only the structures related to the disclosed embodiments are involved. For other structures, reference can be made to the general design. Without conflict, the same embodiment and different embodiments of the present invention can be combined with each other;

[0137] Finally: The above are only the preferred embodiments of the present invention and are not used to limit the present invention. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present invention shall be included within the protection scope of the present invention.

Claims

1. A distributed communication integrated verification method for smart home, characterized in that: include: S1: monitoring and collecting corresponding signals of smart home: real-time monitoring of the signal status of smart devices in the smart home environment when they are running, and collecting the signals sent and received by the smart devices to obtain the first communication signal; S2: Locating the interference source: performing a signal locating operation on the first communication signal corresponding to the signal abnormality, the signal locating operation is used to obtain the second communication signal; S3: Intelligently suppress interference sources: obtain an intelligent anti-interference model, and obtain second signal integration information corresponding to the second communication signal through the second communication signal in the interference source positioning module according to the intelligent anti-interference model; S4: Adapting and extending the communication protocol: identifying the device protocol corresponding to the first communication signal, and optimizing and adjusting the protocol based on the second signal integration information corresponding to the second communication signal to obtain the first signal integration information; S5: Analyze distributed data: Distribute the integrated information of the first signal and obtain a third communication signal based on the overall architecture and operation requirements of the smart home; S6: Evaluate and monitor smart home performance: obtain a smart performance evaluation model, and obtain third signal integration information corresponding to the third communication signal through the third communication signal in the distributed data processing module according to the smart performance evaluation model; S7: Optimize the smart home organizational structure: Perform dynamic verification based on the third signal integration information to verify the performance of the smart home architecture and optimize it.

2. A distributed communication integrated verification method for smart home according to claim 1, characterized in that: The step S2, obtaining a second communication signal, specifically includes: Perform signal positioning operations according to the abnormality type corresponding to the abnormal characteristics and the layout characteristics and distribution of smart home devices. The signal positioning operations include positioning based on signal arrival time difference, signal strength indication positioning, and arrival angle positioning; Determine the configuration parameters in the positioning technology, which include the location coordinates of each monitoring point, the communication signal propagation speed, and the conversion parameters between the signal strength and the distance of the monitoring point.

3. A distributed communication integrated verification method for smart home according to claim 2, characterized in that: The step S2, obtaining a second communication signal, specifically includes: The signal positioning operation is performed based on the signal arrival time difference positioning. According to the signal abnormality corresponding to the first communication signal, that is, the abnormality type corresponding to the abnormal feature, the communication signal transmission timestamp when the communication signal arrives at each monitoring point is extracted. Based on the transmission time t of the communication signal from the monitoring point n to the monitoring point m, the transmission time t m , and the transmission time t of the communication signal from monitoring point m to monitoring point n n , calculate the signal arrival time difference Δt between monitoring point n and monitoring point m mn , specifically expressed as: Δt mn =|t m -t n |, Among them, n and m represent the indexes of different monitoring points, |t m -t n | is expressed as the absolute value of the signal arrival time difference; Based on the position coordinates n (x n ,y n , z n ), the position coordinates of the monitoring point m (x m ,y m , z m ), communication signal propagation speed v, and the signal arrival time difference Δt between monitoring point n and monitoring point m mn , obtain the interference source coordinate objective function F(IS(X, Y, Z)), which is specifically expressed as: F(IS(X,Y,Z))=F mpn 2 (m,n)+F mpn-1 2 (m,n)+…+F1 2 (m,n), Among them, mpn represents the total number of interference source estimation functions, and the value of mpn is C pn 2 , pn represents the total number of monitoring points, that is, the number of combinations of 2 monitoring points taken from the total number of monitoring points pn, and F(m,n) represents the interference source estimation function between monitoring points n and m, which is specifically expressed as: ， Wherein, X, Y, and Z represent the coordinate positions of the interference source IS respectively.

4. A distributed communication integrated verification method for smart home according to claim 1, characterized in that: The step S3, obtaining the second signal integration information, specifically includes: Performing matching analysis on the second communication signal to obtain interference source features corresponding to the second communication signal, where the interference source features are target key features corresponding to the interference source in the second communication signal, and the target key features include interference source type, interference intensity, interference source coordinates, and device identifier to which the interference source belongs; In a preset communication integrated database, an intelligent anti-interference model corresponding to the interference source characteristics is obtained, and the preset communication integrated database is used to store the corresponding relationship between the interference source characteristics and the intelligent anti-interference model.

5. A distributed communication integrated verification method for smart home according to claim 1, characterized in that: The step S4, obtaining the first signal integration information, specifically includes: Establish a protocol compatibility matrix based on the acquired device protocol type and version number. The protocol compatibility matrix is ​​based on a large number of experimental tests and the compatibility relationship between the specific protocols and versions used by the current devices; Verify communications between smart home devices through a protocol compatibility matrix; Performing a protocol optimization and adjustment strategy according to the second signal integration information, the protocol optimization and adjustment strategy including standardizing the protocol format, modifying the protocol data format, conversion rules, adjusting communication parameters, and replacing the protocol conversion plug-in; In a preset communication integrated database, a protocol optimization adjustment strategy corresponding to the protocol compatibility matrix is ​​obtained. The preset communication integrated database is used to store the corresponding relationship between the protocol compatibility matrix and the protocol optimization adjustment strategy.

6. A distributed communication integrated verification method for smart home according to claim 1, characterized in that: The step S5 of acquiring the third communication signal specifically includes: Performing distributed processing based on the first signal integration information, the distributed processing including data partition analysis, parallel processing analysis, and load balancing analysis; The first signal integration information corresponding to the distributed processing is integrated to obtain a third communication signal.

7. A distributed communication integrated verification method for smart home according to claim 6, characterized in that: The step S5 of acquiring the third communication signal specifically includes: Distributed processing is performed using data partitioning, and a classification operation is performed according to the first signal integration information to obtain an allocation rule corresponding to the first signal integration information, where the allocation rule is a target processing partition corresponding to the first signal integration information, and the target processing partition includes device control instructions, device status feedback data, and multimedia data; By using parallel processing for distributed processing, the device communication stability verification task is decomposed into a plurality of subtasks according to the first signal integration information, and verification is performed for different groups of smart home devices; Decompose the data transmission efficiency calculation task into multiple subtasks, each subtask is responsible for calculating the data transmission efficiency between specific devices; Summarize the analysis results of subtasks; Use load balancing for distributed processing, and continuously monitor and analyze the load of each processing node, including the current processing task volume, available resources, and network bandwidth usage of the processing node; An allocation operation is performed based on the load monitoring result and the first signal integration information, and the allocation operation is determined based on the remaining available resources of the processing node, the current processing task volume, and the network bandwidth.

8. A distributed communication integrated verification method for smart home according to claim 1, characterized in that: The step S6, obtaining third signal integration information corresponding to the third communication signal, specifically includes: According to the third communication signal, the performance index corresponding to the third communication signal is calculated by the intelligent performance evaluation model, and the performance index includes the device connection success rate, the data transmission rate, and the average response time. The actual calculated value of the performance index is compared and analyzed with the preset standard value; Comprehensively evaluate the relationship between multiple performance indicators; The third communication signal is received regularly, and the performance index corresponding to the third communication signal is calculated by the intelligent performance evaluation model to obtain the change of the performance index, so as to obtain the third signal integrated information.

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