Intelligent resolution system and method for communicating data

Abstract

The application discloses an intelligent analysis system and method for communication data, and relates to the technical field of data transmission.The system comprises the following steps: obtaining a smart home device list; obtaining target home scene information through interaction, performing device application analysis on the target home scene information, and obtaining a target application home device set; constructing a communication analysis cloud, matching and mapping a home device control model group, and performing resource analysis to obtain a target device control model set; and performing communication control on the target application home device set based on a home device control parameter set.The system solves the technical problem that the existing home device communication data analysis has data islands and insufficient device compatibility, which makes it difficult to accurately match user requirements, and further leads to inaccurate, comprehensive and intelligent analysis and processing of communication data.The system comprehensively captures, intelligently analyzes and accurately controls the communication data between smart home devices, and achieves the technical effects of improving the accuracy and intelligence of communication data analysis.

Description

Technical Field

[0001] The present application relates to the technical field related to data transmission, and in particular to an intelligent parsing system and method for communication data. Background Art

[0002] In today's rapidly developing smart home era, with the deep integration of the Internet of Things, big data and artificial intelligence technologies, people's demand for an intelligent and convenient home environment is growing. As the core carrier of this trend, the smart home system not only requires efficient interconnection between devices, but also needs to realize intelligent analysis and processing of massive communication data to accurately match users' personalized needs and optimize the home scene experience. However, traditional smart home systems often face problems such as inconsistent communication data formats, data silos, poor device compatibility and insufficient intelligence, which makes it difficult for users to enjoy real intelligent services during actual use. At the same time, users' demand for smart homes is often related to specific home scenes, and it is impossible to quickly and accurately match the corresponding home device control model according to user needs, resulting in a poor user experience.

[0003] Therefore, at the current stage, the technologies related to the analysis of communication data of home appliances suffer from data silos and insufficient device compatibility, making it difficult to accurately match user needs, which in turn leads to technical problems in which the analysis and processing of communication data is not accurate, comprehensive, and intelligent enough. Summary of the Invention

[0004] This application provides an intelligent parsing system and method for communication data, which solves the technical problems of data silos and insufficient device compatibility in existing home device communication data parsing, making it difficult to accurately match user needs, and thus resulting in inaccurate, comprehensive and intelligent parsing and processing of communication data. It realizes the comprehensive capture, intelligent analysis and precise control of communication data between smart home devices, and achieves the technical effect of improving the accuracy and intelligence of communication data parsing.

[0005] The present application provides an intelligent parsing system for communication data, the system comprising: a smart home device list acquisition module, configured to acquire a smart home device list, wherein each home device in the smart home device list has a built-in sensor group, and the sensor group is communicatively connected to a data communication module, and a device communication data set of the smart home device list is acquired through the data communication module; a target application home device set acquisition module, configured to interactively acquire target home scene information, perform device application parsing on the target home scene information based on the smart home device list and the device communication data set, and acquire a target application home device set; a communication parsing cloud construction module, configured to construct a communication parsing cloud, acquire a home device control model group based on the communication parsing cloud, and perform matching mapping and resource parsing on the home device control model group based on the target application home device set to acquire a target device control model set; and a home device set communication control module, configured to perform control parsing on the target application home device set based on the target device control model set, determine a home device control parameter set, and perform communication control on the target application home device set based on the home device control parameter set.

[0006] In a possible implementation, the target application home device set acquisition module also performs the following processing: obtaining application scenario factor information, performing demand analysis on the target home scene information based on the application scenario factor information, and obtaining home scene demand pattern parameters; performing pattern matching with the smart home device list based on the home scene demand pattern parameters to obtain a smart home set to be matched; performing device status analysis on the device communication data set according to the home scene demand pattern parameters to determine a device available status set; screening the smart home set to be matched based on the device available status set to obtain the target application home device set.

[0007] In a possible implementation, the communication analysis cloud construction module further performs the following processing: constructing a set of home application scenario instances and a list of home device control analysis algorithms; associating control parameters of each home device in the smart home device list based on the home application scenario instance set to obtain a set of home device scenario-associated control parameters; performing control test analysis on the set of home device scenario-associated control parameters using each analysis algorithm in the list of home device control analysis algorithms to obtain a set of home device algorithm control test data; performing model architecture selection and control model training on the set of home device algorithm control test data through the communication analysis cloud to obtain the home device control model group.

[0008] In a possible implementation, the communication analysis cloud construction module further performs the following processing: matching and mapping the home device control model group based on the target application home device set to obtain a home device control model set for selection; performing multi-dimensional performance verification on the home device control model set for selection to obtain a home device control model performance parameter set; obtaining data analysis computing resources through the communication analysis cloud; performing resource analysis and optimization on the home device control model set for selection based on the data analysis computing resources and the home device control model performance parameter set to obtain the target device control model set.

[0009] In a possible implementation, the communication analysis cloud construction module also performs the following processing: performing computing resource calculation on the set of candidate home device control models based on the set of home device control model performance parameters to obtain a set of required computing resources for the candidate models; obtaining resource allocation balancing factor information, the resource allocation balancing factor information including processing time efficiency balancing and response time balancing; constructing a model fitness matching function based on the data analysis computing resources and the resource allocation balancing factor information; performing fitness analysis on the set of candidate home device control models based on the model fitness matching function to obtain multiple groups of model matching indexes; optimizing the set of candidate home device control models based on the multiple groups of model matching indexes to obtain the target device control model set.

[0010] In a possible implementation, the communication parsing cloud construction module further performs the following processing: the model fitness matching function is specifically:

[0011] ;

[0012] Where C is the model matching index, Characterization X i The matching evaluation function of the processing time balance corresponding to the group model, Characterization X i The matching evaluation function of the response time balance corresponding to the group model, For the Xth i The loading covariance of the group model, parse computing resources for said data, and They are the weight ratios of processing time balance and response time balance respectively.

[0013] In a possible implementation, the intelligent parsing system for communication data further performs the following processing: performing communication control on the target application home device set based on the home device control parameter set to obtain smart home control feedback parameters; if the smart home control feedback parameters do not achieve the preset home device control effect, optimizing and analyzing the smart home control feedback parameters to determine the control parameter fine-tuning variables; fine-tuning and optimizing the smart home control feedback parameters based on the control parameter fine-tuning variables to obtain a home device optimized control parameter set.

[0014] The present application also provides an intelligent parsing method for communication data, the method comprising: obtaining a list of smart home devices, each home device in the smart home device list having a built-in sensor group, and the sensor group being communicatively connected to a data communication module, and obtaining a device communication data set of the smart home device list through the data communication module; interactively obtaining target home scene information, performing device application parsing on the target home scene information based on the smart home device list and the device communication data set to obtain a target application home device set; constructing a communication parsing cloud, obtaining a home device control model group based on the communication parsing cloud, performing matching mapping and resource parsing on the home device control model group based on the target application home device set to obtain a target device control model set; performing control parsing on the target application home device set based on the target device control model set, determining a home device control parameter set, and performing communication control on the target application home device set based on the home device control parameter set.

[0015] The intelligent parsing system and method for communication data proposed in this application is intended to obtain a list of smart home devices; interactively obtain target home scene information, perform device application parsing on the target home scene information, and obtain a target application home device set; build a communication parsing cloud, match and map the home device control model group and perform resource parsing to obtain a target device control model set; and perform communication control on the target application home device set based on the home device control parameter set. This solves the technical problems of data silos and insufficient device compatibility in existing home device communication data parsing, which make it difficult to accurately match user needs, and thus lead to inaccurate, comprehensive, and intelligent parsing and processing of communication data. It achieves comprehensive capture, intelligent analysis, and precise control of communication data between smart home devices, achieving the technical effect of improving the accuracy and intelligence of communication data parsing. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] To more clearly illustrate the technical solutions of the embodiments of the present disclosure, the accompanying drawings of the embodiments of the present disclosure are briefly introduced below. Flowcharts are used in this application to illustrate the operations performed by the systems according to the embodiments of the present application. It should be understood that the preceding or following operations are not necessarily performed in precise order. Instead, various steps may be processed in reverse order or simultaneously as needed. Furthermore, other operations may be added to these processes, or one or more operations may be removed from these processes.

[0017] Figure 1 A schematic diagram of the structure of an intelligent parsing system for communication data provided in an embodiment of the present application;

[0018] Figure 2 A flowchart of an intelligent parsing method for communication data provided in an embodiment of the present application.

[0019] Description of the accompanying drawings: smart home device list acquisition module 10, target application home device set acquisition module 20, communication analysis cloud construction module 30, home device set communication control module 40. DETAILED DESCRIPTION

[0020] The above description is only an overview of the technical solution of the present application. In order to more clearly understand the technical means of the present application, it can be implemented in accordance with the contents of the specification. In order to make the above and other purposes, features and advantages of the present application more obvious and easy to understand, the specific implementation methods of the present application are listed below.

[0021] In order to make the purpose, technical solutions and advantages of this application clearer, the application will be further described in detail below with reference to the accompanying drawings. The described embodiments should not be regarded as limiting this application. All other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of this application.

[0022] In the following description, reference is made to “some embodiments”, which describes a subset of all possible embodiments, but it will be understood that “some embodiments” may be the same subset or different subsets of all possible embodiments and may be combined with each other without conflict, and the terms “first\second” involved are merely used to distinguish similar objects and do not represent a specific ordering of the objects. The terms “including” and “having” and any variations are intended to cover non-exclusive inclusions. For example, a process, system, product, or server that includes a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or modules that are not clearly listed or inherent to these processes, products, or devices. Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the art to which this application belongs. The terms used herein are for the purpose of describing the embodiments of this application only.

[0023] The present application provides an intelligent analysis system for communication data, such as Figure 1 As shown, the system includes:

[0024] The smart home device list acquisition module 10 is used to obtain a list of smart home devices. Each home device in the smart home device list has a built-in sensor group, and the sensor group is communicatively connected to the data communication module, and the device communication data set of the smart home device list is obtained through the data communication module. The smart home device list is a list that includes multiple devices in a smart home system, which may include but is not limited to smart light bulbs, smart sockets, smart door locks, smart cameras, smart thermostats, etc. Each device has specific functions and attributes to meet the different needs of family life. All smart home devices usually have various sensors integrated inside to monitor and collect status information of the surrounding environment or the device itself, forming a sensor group, such as temperature sensors, humidity sensors, light sensors, motion sensors, sound sensors, etc., which can sense and capture relevant data in real time and provide basic information for the intelligent control of the device. The sensor group is communicatively connected to the data communication module, and the device communication data set of the smart home device list is obtained through the data communication module, wherein the data communication module is a component in the smart home device used to communicate with other device systems. As a key component of communication, the data communication module supports various communication protocols (such as Wi-Fi, Zigbee, Bluetooth, etc.) to ensure that the device can stably and reliably transmit and communicate data with other devices or cloud servers. It is responsible for converting the data collected by the sensor group into a transmittable format and sending it to the designated recipient through the network. Each device in the smart home device list will send the data collected by its sensor group to the system (such as a cloud server or a local control center) through the data communication module. These data collections constitute the device communication data collection. The device communication data collection contains the real-time status information of all devices in the smart home system, environmental change data, etc., providing a rich data source for the system's intelligent analysis and control, thereby realizing intelligent monitoring and management of the entire smart home system.

[0025] The target application home device set acquisition module 20 is used to interactively obtain target home scene information, perform device application analysis on the target home scene information based on the smart home device list and the device communication data set, and obtain the target application home device set. The user interacts with the system through the control interface of the smart home system (such as a smartphone APP, smart voice assistant, smart panel, etc.), and clearly expresses or selects the desired home scene, such as the user-defined "away mode", "home mode", "movie viewing mode", etc. Each home scene contains multiple user-preset home device operation instructions. For example, "away mode" may include turning off all lights, TVs, air conditioners and other devices, and starting the security system; "movie viewing mode" may include dimming lights, closing curtains, turning on TVs or projectors, etc. The target home scene information is analyzed for device application based on the smart home device list and the device communication data set. Specifically, first, according to the home scene selected or defined by the user, the devices that need to participate in the scene are identified in the smart home device list, and these home devices should It has been identified and recorded by the system in some way (such as automatic discovery, manual addition, etc.), and then the current status information of each device (such as switch status, temperature setting, brightness, etc.) is obtained through the device communication data set. This information is used to determine whether the home device needs to perform an operation and what operation to perform. Then, based on the smart home device list and the current status of the device, the target home scene information is parsed, including determining which devices need to be activated or adjusted, how to adjust them (such as adjusting brightness, changing temperature, etc.), and the order and priority of operations. Through device application analysis, the target application home device set is obtained. This set includes all devices that need to participate in the current home scene, and may also include the operation instructions that each of these home devices needs to execute, providing users with a more convenient, comfortable and personalized life experience.

[0026] The communication analysis cloud construction module 30 is used to construct a communication analysis cloud, obtain a home device control model group based on the communication analysis cloud, and perform matching mapping and resource analysis on the home device control model group based on the target application home device set to obtain the target device control model set. Constructing a communication analysis cloud refers to designing and building a stable and efficient cloud analysis platform that can support large-scale data processing, real-time communication, and advanced analysis functions. The cloud analysis platform typically includes a data storage layer, a computing processing layer, a communication interface layer, and a user interaction layer. Considering that smart home systems may involve user privacy and home security, the cloud analysis platform must also establish strict security mechanisms, such as data encryption, access control, and authentication, to ensure the security of home communication data transmission and storage. With the continuous increase in smart home devices and the expansion of their functions, the cloud platform needs to have good scalability to easily cope with the possible growth in data volume and user volume in the future. The home device control model is a template stored in the cloud analysis platform that describes how a device responds to control commands. It contains information such as the device's operating interface, parameter range, and status feedback. By defining the control model, standardized control and management of home devices can be achieved. The home device control model group refers to the control model of multiple home devices trained in different algorithms. The cloud platform classifies, indexes and manages the control model collection under the target application home device collection, so that it can quickly retrieve and match when needed; it matches and maps the home device control model group and parses resources. Specifically, the communication parsing cloud performs matching and mapping in the stored home device control model group according to the device information in the target application home device collection, which is similar to searching and matching records in a database. The purpose is to find the device control model corresponding to each device. After finding the corresponding control model, these models are parsed for resources, including the operation interface, parameter range, status feedback and other information in the parsed model to determine how to perform specific control operations on the device. At the same time, it is necessary to comprehensively consider multiple factors such as the current status of the home device, user preferences, and environmental conditions. After matching, mapping and resource parsing, the communication parsing cloud generates a target device control model collection, which includes all devices that need to participate in the current home scene and their corresponding device control models, and then realizes the user's expected home scene effect through the device control model.

[0027] The home device set communication control module 40 is used to control and parse the target application home device set based on the target device control model set, determine the home device control parameter set, and perform communication control on the target application home device set based on the home device control parameter set. The target application home device set is controlled and parsed based on the target device control model set. Specifically, according to each control model in the target device control model set, the control logic, operation interface and parameter requirements of each device in a specific scenario are deeply understood, including determining which devices need to be activated or adjusted, how to adjust them (such as adjusting brightness, changing temperature, etc.), and the order and priority of operations. Based on these analysis results, the specific control parameters of each device are further determined. These control parameters are used to perform operational control of home devices, such as brightness level, temperature setting value, switch status, etc. The control parameters of these devices are combined into a set, namely the home device control parameter set, which contains the control parameter information of all home devices in the current home scene. And perform parameter verification on it, such as checking whether the control parameters are within the range supported by the device and whether they meet the user preferences; based on the home device control parameter set, generate specific home device control instructions, which may include the identification information of the home device, the type of operation to be performed, and the corresponding device control parameters, etc., and then transmit the device control instructions to each home device in the target application home device set through the data communication module. After receiving the device control instructions, these home devices perform corresponding control operations according to the device control parameters in the device control instructions. For example, smart light bulbs may be adjusted to a specified brightness level according to the instructions; smart air conditioners may be adjusted to the temperature set by the user according to the instructions, etc., thereby realizing precise control and intelligent management of home devices.

[0028] The intelligent communication data parsing system according to an embodiment of the present invention is designed to address the technical issues of data silos and insufficient device compatibility in existing home device communication data parsing, which hinder accurate matching with user needs and, in turn, result in inaccurate, comprehensive, and intelligent communication data parsing. The system enables comprehensive capture, intelligent analysis, and precise control of communication data between smart home devices, achieving the technical effect of improving the accuracy and intelligence of communication data parsing. The intelligent communication data parsing system includes a smart home device list acquisition module 10, a target application home device set acquisition module 20, a communication parsing cloud construction module 30, and a home device set communication control module 40.

[0029] The specific configuration of the target application home device set acquisition module 20 will be described in detail below. The target application home device set acquisition module 20 may further include: obtaining application scenario factor information, performing demand analysis on the target home scene information based on the application scenario factor information, and obtaining home scene demand pattern parameters. Various factor information related to smart home application scenarios is collected and analyzed, which may include the size, layout, lighting conditions, temperature, humidity, air quality, daily living habits of family members, safety needs, and comfort requirements of the user's living space. These application scenario factor information is then analyzed to identify the user's specific needs in the home scene, including obtaining different scene modes, such as waking up mode, leaving home mode, returning home mode, and movie viewing mode, and determining corresponding needs for each mode, that is, determining the home scene demand pattern parameters corresponding to each mode, which describe how the user wants the smart home system to respond and provide services in different scenarios. For example, in "movie viewing mode", the user may want the lights to automatically dim to a certain brightness, the curtains to automatically close, and the audio system to automatically play movie sound effects.

[0030] The method further includes pattern matching based on the home scene demand pattern parameters and the smart home device list to obtain a set of smart homes to be matched. Matching is performed based on the home scene demand pattern parameters and the smart home device list. Specifically, the home scene demand pattern parameters are parsed to clarify the user's functional and status requirements for the device in the scenario. Based on the results of the demand analysis, the smart home device list is traversed to check whether the function and control interface of each device match the demand pattern parameters. The matching criteria may include the type of device (such as lighting, air conditioning, curtains, etc.), the control range (such as brightness adjustment, temperature setting, etc.), and whether a specific linkage protocol or control instruction is supported. All devices that meet the requirements of the demand pattern parameters together constitute the set of smart homes to be matched, which includes all devices that can participate in the current home scene, and their status and functions have been pre-configured according to the user's requirements.

[0031] The system also includes performing a device state analysis on the device communication data set according to the home scenario demand pattern parameters to determine a device available state set. The system analyzes the device communication data set according to the home scenario demand pattern parameters, i.e., analyzes information such as the device's current state (e.g., on / off state, temperature setting, brightness level, etc.), connection status (whether online), and battery level, assesses the availability and applicability of each device, and determines a device available state set to further determine which devices are actually available to meet specific home scenario requirements.

[0032] The method further includes filtering the to-be-matched smart home device set based on the device availability set to obtain the target application home device set. Based on the device availability set, the to-be-matched smart home device set is further filtered. The filtering process considers factors such as the current state of the device, whether it meets the requirements of the demand model parameters, and the compatibility and interoperability between the devices to obtain the target application home device set. The devices in this set are considered to be most suitable for the current application scenario and can meet the user's home scenario requirements.

[0033] The specific configuration of the communication analysis cloud construction module 30 will be described in detail below. The communication analysis cloud construction module 30 can further include: constructing a set of home application scenario instances and a list of home device control analysis algorithms. The set of home application scenario instances may include "away mode", "return home mode", "movie viewing mode", "sleep mode", etc. Each scenario instance contains a series of specific device control requirements and behavior patterns; the list of home device control analysis algorithms contains a series of algorithms for analyzing and optimizing smart home device control, such as machine learning algorithms (used to predict user behavior and automatically adjust device status), optimization algorithms (used to allocate resources among multiple devices to achieve the best effect), and rule engines (used to automatically execute device control instructions according to preset rules). Specifically, different furniture devices have different control objectives, and the corresponding control algorithms are different, and the accuracy, performance, and effect of the trained control models are also different.

[0034] The method further includes associating control parameters for each home device in the smart home device list based on the set of home application scenario instances to obtain a set of home device scene-associated control parameters. Based on the set of home application scenario instances, control parameters are associated with each smart home device in each scene. Specifically, corresponding control parameters are set and associated for each smart home device in each scene, thereby forming a set that includes all devices and their corresponding specific control parameters, such as the device's on / off status, operating mode, and setting value (brightness, temperature, wind speed), etc.

[0035] The method further includes performing control test analysis on the set of control parameters associated with the home device scenarios using each analysis algorithm in the list of home device control analysis algorithms to obtain a set of home device algorithm control test data. Using each analysis algorithm in the list of home device control analysis algorithms, the method performs control test analysis on the set of control parameters associated with the home device scenarios, including simulating scenario execution, collecting device response data, and evaluating control effects. Through test analysis, various data is collected, including device state changes and control command execution status, to obtain a set of home device algorithm control test data, including control parameters and control effect data, reflecting the control effects of different algorithms in different scenarios.

[0036] The method further includes selecting a model architecture and performing control model training on the home device algorithm control test data set via the communication analysis cloud to obtain the home device control model group. The home device algorithm control test data set is used as training data for different control models and preprocessed, including data cleaning, feature extraction, and data normalization. The preprocessed data is then used to train the selected different model architectures. During the training process, model parameters are continuously adjusted and algorithms are optimized to obtain a home device control model group. These home device control models can automatically adjust and control the status of smart home devices based on different home scenarios and user needs.

[0037] The specific configuration of the communication parsing cloud-based construction module 30 will be described in detail below. The communication parsing cloud-based construction module 30 may further include: matching and mapping the home device control model group based on the target application home device set to obtain a set of candidate home device control models. The target application home device set is matched and mapped with the existing home device control model group. Based on the device type, function, control requirements, etc., the home device control model that best matches each target device is found from the home device control model group. This results in a set of candidate home device control models for the target device set, which includes all control models that may be applicable to the target device.

[0038] The method further includes performing multi-dimensional performance verification on the set of candidate home device control models to obtain a set of home device control model performance parameters. Each device control model in the set of candidate home device control models is subjected to multi-dimensional performance verification, which may include control accuracy, response time, stability, etc. Through verification, performance parameters of each model in various dimensions are obtained to form a set of home device control model performance parameters.

[0039] The system also includes obtaining data analysis and computing resources from the cloud through the communication analysis. The system utilizes the communication module in the smart home system to transmit and analyze data with the cloud, ensuring access to various resources and services provided by the cloud. The system also obtains necessary data analysis and computing resources from the cloud, which may include computing power, storage capacity, and algorithm libraries. Based on the current task requirements and the cloud's resource availability, computing resources are rationally allocated to ensure smooth performance verification and model optimization.

[0040] The method further includes performing resource parsing and optimization on the set of candidate home device control models based on the data parsing computing resources and the set of home device control model performance parameters to obtain the target device control model set. Based on the acquired data parsing computing resources and the set of home device control model performance parameters, resource parsing is performed on each candidate model, including evaluation of model complexity, computational effort, resource consumption, and other aspects. Based on the parsing results and the requirements of the actual application scenario, an optimization strategy is formulated, and ultimately, the control model that best suits the current target device set is selected from the candidate model set to form the target device control model set. This not only improves the intelligence level and user experience of the smart home system, but also optimizes the system's resource utilization efficiency and performance.

[0041] The specific configuration of the communication parsing cloud-based construction module 30 will be described in detail below. The communication parsing cloud-based construction module 30 may further include: performing computational resource calculations on the set of candidate home device control models based on the set of home device control model performance parameters to obtain a set of required computational resources for the candidate models. Based on the set of home device control model performance parameters (e.g., control accuracy, stability, energy consumption, etc.), the performance of each candidate model in actual applications is evaluated. Based on the performance parameters and complexity of each candidate model, the required computational resources (e.g., CPU time, memory usage, network bandwidth, etc.) are calculated to form a set of required computational resources for the candidate models.

[0042] It also includes obtaining resource allocation balancing factor information, which includes processing time balance and response time balance. Resource allocation balancing factor information is obtained to ensure that the system can reasonably allocate resources between different devices and tasks to optimize overall performance and user experience. Resource allocation balancing factor information includes processing time balance and response time balance. Specifically, processing time balance refers to the ability to maintain a relatively balanced processing speed or efficiency when processing multiple tasks or managing multiple devices. In a smart home system, it means that the system should be able to intelligently allocate computing resources, memory resources, network resources, etc. to ensure that each device and function can be processed in a timely and effective manner; response time balance focuses on the response speed to user requests or device events, and ensures that this response speed remains relatively balanced between different devices and tasks. In a smart home system, users may interact with the system through different devices (such as smartphones, voice assistants, control panels, etc.) and expect to receive a fast and consistent response.

[0043] The process also includes constructing a model fitness matching function based on the data parsing computing resources and the resource allocation balancing factor information. This function combines the required computing resources of the candidate models, the resource allocation balancing factor information (processing time balance and response time balance), and the available data parsing computing resources to construct a model fitness matching function to evaluate the fitness and performance of each candidate model under the current resource conditions.

[0044] The method further includes performing a fitness analysis on the set of candidate home device control models based on the model fitness matching function to obtain multiple sets of model matching indices. Using the constructed model fitness matching function, fitness analysis is performed on the set of candidate home device control models. Considering multiple factors such as the device control model's performance, resource requirements, and resource allocation balance, a model matching index is generated for each candidate device control model. This index comprehensively reflects the model's fitness and performance under current resource conditions.

[0045] The method further includes optimizing the set of candidate home device control models based on the multiple sets of model matching indices to obtain the target device control model set. Based on the fitness analysis results, multiple sets of model matching indices are obtained, each set of indices corresponding to a candidate model. Based on the multiple sets of model matching indices, an optimization operation is performed, such as comparing the matching indices of different models, considering cost-effectiveness, and meeting specific performance requirements. Ultimately, the optimal model combination is selected from the candidate model set to form the target device control model set, which is used to actually control smart home devices, achieve efficient, stable, and intelligent home control, and meet various user needs.

[0046] The following will continue to describe in detail the specific configuration of the communication analysis cloud construction module 30. The communication analysis cloud construction module 30 may further include: the model fitness matching function is specifically:

[0047]

[0048] Where C is the model matching index, Characterization X i The matching evaluation function of the processing time balance corresponding to the group model, Characterization X i The matching evaluation function of the response time balance corresponding to the group model, is the load covariance of the Xi group model, parse computing resources for said data, and The weights of processing time balance and response time balance are respectively. The larger the data analysis computing resources U, the greater the corresponding model matching index.

[0049] The specific configuration of the intelligent parsing system for communication data will be described in detail below. The intelligent parsing system for communication data can further include: performing communication control on the target application home device set based on the home device control parameter set to obtain smart home control feedback parameters. Through its built-in communication module and protocol, the instructions in the control parameter set are sent to the target application home device set, instructing them to operate according to the preset parameters. After the home device receives and executes the control instruction, it sends feedback parameters to the smart home system to reflect the current working status of the device and the execution results, such as actual temperature, humidity, brightness value, etc. By receiving and analyzing these feedback parameters, the real-time operation status and control effect of the home device can be understood in real time.

[0050] The process also includes optimizing and analyzing the smart home control feedback parameters and determining fine-tuning variables for the control parameters if the smart home control feedback parameters do not achieve the preset home device control effects. The smart home control feedback parameters are compared with the preset home device control effects. If the feedback parameters do not achieve the preset control effects, it indicates that there may be a problem with the current control parameter set and optimization and adjustment are required. The smart home control feedback parameters that do not achieve the preset control effects are then analyzed in depth to identify possible causes and determine which control parameters require adjustment, as well as the direction and magnitude of the adjustments, i.e., determining fine-tuning variables for the control parameters.

[0051] The method further includes fine-tuning and optimizing the smart home control feedback parameters based on the control parameter fine-tuning variables to obtain a set of optimized control parameters for home appliances. Based on the control parameter fine-tuning variables, the smart home control feedback parameters are fine-tuned, and through iterative adjustment and optimization, the ideal control effect is gradually approached. Specifically, during the fine-tuning process, the control parameters are adjusted multiple times based on actual feedback and effect evaluation results. After fine-tuning and optimization, a set of optimized control parameters for home appliances that better meet the preset control effect is obtained. This set of parameters is used for subsequent smart home control, thereby improving the control accuracy and stability of the system and providing users with a more comfortable and convenient smart home experience.

[0052] In the above, refer to Figure 1 The intelligent parsing system for communication data according to the embodiment of the present invention is described in detail. Figure 2 An intelligent parsing method for communication data according to an embodiment of the present invention is described.

[0053] Intelligent parsing methods for communication data, such as Figure 2As shown, the method includes: obtaining a list of smart home devices, each home device in the smart home device list has a built-in sensor group, and the sensor group is communicatively connected to a data communication module, and a device communication data set of the smart home device list is obtained through the data communication module; interactively obtaining target home scene information, performing device application analysis on the target home scene information based on the smart home device list and the device communication data set, and obtaining a target application home device set; constructing a communication analysis cloud, obtaining a home device control model group according to the communication analysis cloud, and performing matching mapping and resource analysis on the home device control model group based on the target application home device set to obtain a target device control model set; performing control analysis on the target application home device set based on the target device control model set, determining a home device control parameter set, and performing communication control on the target application home device set based on the home device control parameter set.

[0054] In one possible implementation, obtaining the target application home device set includes: obtaining application scenario factor information, performing demand analysis on the target home scene information based on the application scenario factor information, and obtaining home scene demand pattern parameters; performing pattern matching with the smart home device list based on the home scene demand pattern parameters to obtain a smart home set to be matched; performing device status analysis on the device communication data set according to the home scene demand pattern parameters to determine a device available status set; and screening the smart home set to be matched based on the device available status set to obtain the target application home device set.

[0055] In one possible implementation, the obtaining of the home appliance control model group based on the communication analysis cloud includes: constructing a home application scenario instance set and a home appliance control analysis algorithm list; associating control parameters of each home appliance in the smart home device list based on the home application scenario instance set to obtain a home appliance scenario-associated control parameter set; performing control test analysis on the home appliance scenario-associated control parameter set using each analysis algorithm in the home appliance control analysis algorithm list to obtain a home appliance algorithm control test data set; performing model architecture selection and control model training on the home appliance algorithm control test data set through the communication analysis cloud to obtain the home appliance control model group.

[0056] In one possible implementation, obtaining the target device control model set includes: matching and mapping the home device control model group based on the target application home device set to obtain a home device control model set for selection; performing multi-dimensional performance verification on the home device control model set for selection to obtain a home device control model performance parameter set; obtaining data analysis and computing resources from the cloud through the communication analysis; performing resource analysis and optimization on the home device control model set for selection based on the data analysis and computing resources and the home device control model performance parameter set to obtain the target device control model set.

[0057] In one possible implementation, obtaining the target device control model set includes: performing computing resource calculation on the home device control candidate model set based on the home device control model performance parameter set to obtain the candidate model demand computing resource set; obtaining resource allocation balance factor information, the resource allocation balance factor information including processing time balance and response time balance; constructing a model fitness matching function based on the data analysis computing resources and the resource allocation balance factor information; performing fitness analysis on the home device control candidate model set based on the model fitness matching function to obtain multiple groups of model matching indexes; optimizing the home device control candidate model set based on the multiple groups of model matching indexes to obtain the target device control model set.

[0058] In a possible implementation, performing fitness analysis on the set of candidate home appliance control models based on the model fitness matching function to obtain multiple groups of model matching indexes includes: the model fitness matching function is specifically:

[0059]

[0060] Where C is the model matching index, Characterization X i The matching evaluation function of the processing time balance corresponding to the group model, Characterization X i The matching evaluation function of the response time balance corresponding to the group model, For the Xth i The loading covariance of the group model, parse computing resources for said data, and They are the weight ratios of processing time balance and response time balance respectively.

[0061] In one possible implementation, the intelligent parsing method for communication data further includes: performing communication control on the target application home device set based on the home device control parameter set to obtain smart home control feedback parameters; if the smart home control feedback parameters do not achieve the preset home device control effect, optimizing and analyzing the smart home control feedback parameters to determine the control parameter fine-tuning variables; fine-tuning and optimizing the smart home control feedback parameters based on the control parameter fine-tuning variables to obtain a home device optimized control parameter set.

[0062] The intelligent parsing system for communication data provided by the embodiment of the present invention can execute the intelligent parsing method for communication data provided by any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of the execution method.

[0063] Although the present application makes various references to certain modules in the system according to the embodiments of the present application, any number of different modules may be used and run on the user terminal and / or server, and the various units and modules included are only divided according to functional logic, but are not limited to the above division, as long as the corresponding functions can be achieved; in addition, the specific names of the functional units are only for the convenience of distinguishing each other and are not used to limit the scope of protection of the present invention.

[0064] The above specific embodiments do not constitute a limitation on the scope of protection of this application. Those skilled in the art should understand that various modifications, combinations, and substitutions may be made based on design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this application shall be included within the scope of protection of this application.

Claims

1. An intelligent analysis system for communication data, characterized in that: The system comprises: A smart home device list acquisition module is used to acquire a list of smart home devices, wherein each home device in the smart home device list has a built-in sensor group, and the sensor group is communicatively connected to the data communication module, and a device communication data set of the smart home device list is acquired through the data communication module; A target application home device set acquisition module is used to interactively obtain target home scene information, perform device application analysis on the target home scene information based on the smart home device list and the device communication data set, and obtain a target application home device set; A communication parsing cloud construction module is used to construct a communication parsing cloud, obtain a home device control model group based on the communication parsing cloud, and perform matching mapping and resource parsing on the home device control model group based on the target application home device set to obtain a target device control model set; a home device set communication control module, configured to perform control analysis on the target application home device set based on the target device control model set, determine a home device control parameter set, and perform communication control on the target application home device set based on the home device control parameter set; The steps performed by the communication analysis cloud construction module include: Performing computational resource calculation on a set of candidate home appliance control models based on a set of home appliance control model performance parameters to obtain a set of required computational resources for the candidate models; Acquiring resource allocation balancing factor information, wherein the resource allocation balancing factor information includes processing time efficiency balancing and response time balancing; Constructing a model fitness matching function based on data analysis computing resources and the resource allocation balancing factor information; Performing fitness analysis on the set of candidate home appliance control models based on the model fitness matching function to obtain multiple groups of model matching indexes; Optimizing the set of candidate home appliance control models based on the multiple sets of model matching indexes to obtain the target appliance control model set; The model fitness matching function is specifically: Where C is the model matching index, Characterization X i The matching evaluation function of the processing time balance corresponding to the group model, Characterization X i The matching evaluation function of the response time balance corresponding to the group model, For the Xth i The loading covariance of the group model, parse computing resources for said data, and They are the weight ratios of processing time balance and response time balance respectively.

2. The intelligent analysis system for communication data according to claim 1, characterized in that: The target application home appliance set acquisition module performs the following steps: Acquiring application scenario factor information, and performing demand analysis on the target home scene information based on the application scenario factor information to obtain home scene demand pattern parameters; Performing pattern matching based on the home scene demand pattern parameters and the smart home device list to obtain a set of smart homes to be matched; Performing device status analysis on the device communication data set according to the home scene demand pattern parameters to determine a device available state set; The to-be-matched smart home device set is filtered based on the device available status set to obtain the target application home device set.

3. The intelligent analysis system for communication data according to claim 1, wherein: The steps performed by the communication analysis cloud construction module include: Build a collection of home application scenario examples and a list of home device control analysis algorithms; Associating control parameters of each home appliance in the smart home appliance list based on the home application scenario instance set to obtain a home appliance scenario-associated control parameter set; Performing control test analysis on the home appliance scene-associated control parameter set using each analysis algorithm in the home appliance control analysis algorithm list to obtain a home appliance algorithm control test data set; The home appliance control model group is obtained by performing model architecture selection and control model training on the home appliance algorithm control test data set through the communication analysis cloud.

4. The intelligent analysis system for communication data according to claim 1, characterized in that: The steps performed by the communication analysis cloud construction module include: Matching and mapping the home appliance control model group based on the target application home appliance set to obtain a home appliance control model set to be selected; Performing multi-dimensional performance verification on the set of candidate home appliance control models to obtain a set of home appliance control model performance parameters; Obtaining data analysis and computing resources through the communication analysis cloud; Based on the data analysis and computing resources and the home appliance control model performance parameter set, resource analysis and optimization are performed on the home appliance control candidate model set to obtain the target device control model set.

5. The intelligent analysis system for communication data according to claim 1, characterized in that: The system comprises: Performing communication control on the target application home device set based on the home device control parameter set to obtain smart home control feedback parameters; If the smart home control feedback parameters do not achieve the preset home device control effect, optimizing and analyzing the smart home control feedback parameters to determine the control parameter fine-tuning variables; The smart home control feedback parameters are fine-tuned and optimized based on the control parameter fine-tuning variables to obtain a set of optimized control parameters for home appliances.

6. An intelligent parsing method for communication data, characterized in that: The method is applied to the intelligent analysis system for communication data according to any one of claims 1 to 5, and the method comprises: Obtaining a list of smart home devices, wherein each home device in the list has a built-in sensor group, and the sensor group is communicatively connected to a data communication module, and a device communication data set of the smart home device list is obtained through the data communication module; Interactively obtain target home scene information, perform device application analysis on the target home scene information based on the smart home device list and the device communication data set, and obtain a target application home device set; Building a communication parsing cloud, obtaining a home device control model group according to the communication parsing cloud, and performing matching mapping and resource parsing on the home device control model group based on the target application home device set by the communication parsing cloud to obtain a target device control model set; The target application home appliance set is subjected to control analysis based on the target device control model set, a home appliance control parameter set is determined, and communication control is performed on the target application home appliance set based on the home appliance control parameter set.

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