Smart watch data transmission method and device, storage medium, computer program product and smart watch

Abstract

The application relates to the technical field of medical health, and in particular to a smart watch data transmission method and device, a storage medium, a computer program product and a smart watch. The method comprises the following steps: acquiring multi-source physiological monitoring data collected by a smart watch terminal, and performing data processing on the multi-source physiological monitoring data to generate a to-be-transmitted data object; performing terminal-side state recognition processing based on the to-be-transmitted data object, and determining a data state identifier corresponding to the to-be-transmitted data object; determining a transmission control strategy corresponding to the to-be-transmitted data object according to the data state identifier and current communication environment information; encapsulating the to-be-transmitted data object based on the transmission control strategy and sending the to-be-transmitted data object to a remote data processing platform; receiving strategy adjustment information generated by the remote data processing platform, and updating a data processing process of a subsequent to-be-transmitted data object and the transmission control strategy according to the strategy adjustment information.

Description

Technical Field

[0001] This application relates to the field of medical and health technology, and in particular to a data transmission method, device, storage medium, computer program product, and smartwatch for smartwatches. Background Technology

[0002] With the development of wearable device technology, smartwatches have gradually been applied to the field of remote medical monitoring. By integrating heart rate sensors, blood oxygen detection modules, motion monitoring units, and sleep monitoring components, they can continuously collect multi-source physiological parameters of users and upload the monitoring data to a remote medical platform for analysis and intervention by doctors or health management systems, thereby achieving long-term health monitoring and chronic disease management. In existing technologies, smartwatches typically use a fixed data upload mechanism, that is, sending the collected physiological data directly to the cloud server according to a preset time interval or a unified communication protocol. However, in practical applications, due to limitations in battery capacity, computing resources, and wireless communication conditions, the data transmission process of wearable devices is easily affected by factors such as communication network fluctuations, changes in terminal operating status, and differences in the importance of the data. On the other hand, existing data transmission schemes usually lack a dynamic control mechanism based on joint decision-making based on data content status and communication environment. Data encapsulation methods and transmission strategies are relatively simple, making it difficult to adaptively adjust according to different physiological monitoring scenarios. Furthermore, the remote platform and the terminal mostly adopt a one-way data upload mode, lacking a closed-loop adjustment mechanism that uses platform analysis results to optimize the terminal-side data processing and transmission strategies, resulting in poor overall efficiency and reliability of system data transmission. Therefore, improving the efficiency and reliability of data transmission in smartwatches has become a pressing technical problem that needs to be solved. Summary of the Invention

[0003] The main objective of this application is to provide a data transmission method, device, storage medium, computer program product, and smartwatch for smartwatches, aiming to solve the technical problem of how to improve the efficiency and reliability of data transmission in smartwatches.

[0004] To achieve the above objectives, this application provides a data transmission method for a smartwatch. The method is applied to a data transmission system comprising a smartwatch terminal, a remote data processing platform, and a communication network. The method includes: Acquire multi-source physiological monitoring data collected by the smartwatch terminal, and process the multi-source physiological monitoring data to generate a data object to be transmitted; Based on the data object to be transmitted, perform terminal-side status recognition processing to determine the data status identifier corresponding to the data object to be transmitted. Based on the data status identifier and the current communication environment information, determine the transmission control strategy corresponding to the data object to be transmitted; The data object to be transmitted is encapsulated based on the transmission control strategy and sent to the remote data processing platform; The system receives policy adjustment information generated by the remote data processing platform and updates the subsequent data processing procedure for the data object to be transmitted and the transmission control policy based on the policy adjustment information.

[0005] In one embodiment, the step of acquiring multi-source physiological monitoring data collected by a smartwatch terminal and processing the multi-source physiological monitoring data to generate a data object to be transmitted includes: Acquire multi-source physiological monitoring data collected by a smartwatch terminal, and perform signal preprocessing on the multi-source physiological monitoring data to obtain preprocessed physiological data after removing interference components; Based on the preprocessed physiological data, feature extraction processing is performed to obtain a set of feature parameters; The set of feature parameters is compressed and structured to generate the data object to be transmitted.

[0006] In one embodiment, the step of performing terminal-side state recognition processing based on the data object to be transmitted to determine the data state identifier corresponding to the data object to be transmitted includes: The data object to be transmitted is parsed to extract physiological feature information, time correlation information and data source identification information, and a feature input dataset for state determination is constructed. The feature input dataset is input into a preset recognition model for state reasoning processing to obtain a state determination result corresponding to the data object to be transmitted. The state reasoning processing is based on the analysis of the combination relationship between the physiological feature information and the time correlation information. Based on the status determination result, a data status identifier associated with the data object to be transmitted is generated.

[0007] In one embodiment, the step of determining the transmission control strategy corresponding to the data object to be transmitted based on the data status identifier and the current communication environment information includes: Obtain communication environment information related to the transmission process of the data object to be transmitted, and perform state characterization processing on the communication environment information to obtain a set of communication environment parameters; Based on the data status identifier and the communication environment parameter set, a strategy matching process is performed to determine candidate transmission strategies from a preset transmission strategy set, wherein the candidate transmission strategies include control parameters related to transmission path selection and data protection methods; The candidate transmission strategies are processed to determine the transmission control strategy associated with the data object to be transmitted.

[0008] In one embodiment, the step of encapsulating the data object to be transmitted based on the transmission control strategy and sending it to the remote data processing platform includes: Based on the transmission control strategy, the data encapsulation parameters corresponding to the data object to be transmitted are determined, and the data object to be transmitted is subjected to structured encapsulation processing based on the data encapsulation parameters to generate a data packet to be sent. Based on the transmission control strategy, the data packet to be sent is processed for transmission configuration to determine the corresponding transmission path information and data protection parameters, thereby obtaining the target data to be sent. Based on the transmission path information, the target data is sent to the remote data processing platform through the communication network.

[0009] In one embodiment, the step of receiving policy adjustment information generated by the remote data processing platform and updating the subsequent data processing procedure for the data object to be transmitted and the transmission control policy based on the policy adjustment information includes: The system receives policy adjustment information sent by the remote data processing platform and parses the policy adjustment information to obtain a set of adjustment parameters related to data processing rules and transmission control rules. Based on the set of adjustment parameters, the current terminal-side configuration is updated to generate updated data processing parameters and updated transmission control parameters. The data processing procedure for the subsequent data objects to be transmitted is adjusted based on the updated data processing parameters, and the transmission control strategy corresponding to the subsequent data objects to be transmitted is updated based on the updated transmission control parameters.

[0010] Furthermore, to achieve the above objectives, this application also proposes a smartwatch data transmission device, which is applied to a data transmission system consisting of a smartwatch terminal, a remote data processing platform, and a communication network. The smartwatch data transmission device includes: The monitoring data processing module is used to acquire multi-source physiological monitoring data collected by the smartwatch terminal, and to process the multi-source physiological monitoring data to generate a data object to be transmitted. The status identification module is used to perform terminal-side status identification processing based on the data object to be transmitted, and to determine the data status identifier corresponding to the data object to be transmitted. The transmission control module is used to determine the transmission control strategy corresponding to the data object to be transmitted based on the data status identifier and the current communication environment information. An encapsulation and transmission module is used to encapsulate the data object to be transmitted based on the transmission control strategy and send it to the remote data processing platform. The target module is used to receive policy adjustment information generated by the remote data processing platform, and update the subsequent data processing process of the data object to be transmitted and the transmission control policy according to the policy adjustment information.

[0011] Furthermore, to achieve the above objectives, this application also proposes a smartwatch, which includes: a memory, a processor, and a smartwatch data transmission program stored in the memory and executable on the processor, wherein the smartwatch data transmission program is configured to implement the steps of the smartwatch data transmission method as described in any of the above embodiments.

[0012] In addition, to achieve the above objectives, this application also proposes a storage medium storing a smartwatch data transmission program, which, when executed by a processor, implements the steps of the smartwatch data transmission method described above.

[0013] In addition, to achieve the above objectives, this application also proposes a computer program product, which includes a computer program that, when executed by a processor, implements the steps of the smartwatch data transmission method described above.

[0014] This application acquires multi-source physiological monitoring data collected by a smartwatch terminal, processes the multi-source physiological monitoring data to generate a data object to be transmitted; performs terminal-side state recognition processing based on the data object to be transmitted to determine the data status identifier corresponding to the data object to be transmitted; determines the transmission control strategy corresponding to the data object to be transmitted based on the data status identifier and the current communication environment information; encapsulates the data object to be transmitted based on the transmission control strategy and sends it to a remote data processing platform; receives strategy adjustment information generated by the remote data processing platform, and updates the subsequent data processing process and transmission control strategy of the data object to be transmitted based on the strategy adjustment information. This application generates a data object to be transmitted by processing multi-source physiological monitoring data collected from a smartwatch terminal. Based on the data object, the terminal-side status is identified to determine the data status identifier. Then, the corresponding transmission control strategy is determined by combining the data status identifier with the current communication environment information, enabling the data transmission process to adaptively adjust according to data characteristics and communication conditions. Simultaneously, the data object to be transmitted is encapsulated and sent based on the transmission control strategy, and the strategy adjustment information generated by the remote data processing platform is received to dynamically update the subsequent data processing process and transmission control strategy, forming a feedback optimization mechanism for the transmission strategy. This improves the utilization rate of communication resources while ensuring the reliability of key data transmission, achieving a synergistic improvement in the data transmission efficiency and reliability of the smartwatch. Attached Figure Description

[0015] Figure 1This is a flowchart illustrating the first embodiment of the smartwatch data transmission method of this application; Figure 2 This is a schematic diagram of a sub-process in the second embodiment of the smartwatch data transmission method of this application; Figure 3 This is a schematic diagram of a sub-process in the third embodiment of the smartwatch data transmission method of this application; Figure 4 This is a schematic diagram of the module structure of the smartwatch data transmission device according to an embodiment of this application; Figure 5 This is a schematic diagram of the device structure of the hardware operating environment involved in the smartwatch data transmission method in this application embodiment.

[0016] The realization of the purpose, functional features and advantages of this application will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0017] It should be understood that the specific embodiments described herein are for illustrative purposes only and are not intended to limit the scope of this application.

[0018] To better understand the technical solution of this application, a detailed description will be provided below in conjunction with the accompanying drawings and specific implementation methods.

[0019] With the development of wearable device technology, smartwatches have gradually been applied to the field of remote medical monitoring. By integrating heart rate sensors, blood oxygen detection modules, motion monitoring units, and sleep monitoring components, they can continuously collect multi-source physiological parameters of users and upload the monitoring data to a remote medical platform for analysis and intervention by doctors or health management systems, thereby achieving long-term health monitoring and chronic disease management. In existing technologies, smartwatches typically use a fixed data upload mechanism, that is, sending the collected physiological data directly to the cloud server according to a preset time interval or a unified communication protocol. However, in practical applications, due to limitations in battery capacity, computing resources, and wireless communication conditions, the data transmission process of wearable devices is easily affected by factors such as communication network fluctuations, changes in terminal operating status, and differences in the importance of the data. On the other hand, existing data transmission schemes usually lack a dynamic control mechanism based on joint decision-making based on data content status and communication environment. Data encapsulation methods and transmission strategies are relatively simple, making it difficult to adaptively adjust according to different physiological monitoring scenarios. Furthermore, the remote platform and the terminal mostly adopt a one-way data upload mode, lacking a closed-loop adjustment mechanism that uses platform analysis results to optimize the terminal-side data processing and transmission strategies, resulting in poor overall efficiency and reliability of system data transmission. Therefore, improving the efficiency and reliability of data transmission in smartwatches has become a pressing technical problem that needs to be solved.

[0020] The main solution of this application is as follows: acquiring multi-source physiological monitoring data collected by a smartwatch terminal, and processing the multi-source physiological monitoring data to generate a data object to be transmitted; performing terminal-side state recognition processing based on the data object to be transmitted to determine the data status identifier corresponding to the data object to be transmitted; determining the transmission control strategy corresponding to the data object to be transmitted based on the data status identifier and the current communication environment information; encapsulating the data object to be transmitted based on the transmission control strategy and sending it to a remote data processing platform; receiving strategy adjustment information generated by the remote data processing platform, and updating the subsequent data processing process and transmission control strategy of the data object to be transmitted based on the strategy adjustment information.

[0021] This application generates a data object to be transmitted by processing multi-source physiological monitoring data collected from a smartwatch terminal. Based on the data object, the terminal-side status is identified to determine the data status identifier. Then, the corresponding transmission control strategy is determined by combining the data status identifier with the current communication environment information, enabling the data transmission process to adaptively adjust according to data characteristics and communication conditions. Simultaneously, the data object to be transmitted is encapsulated and sent based on the transmission control strategy, and the strategy adjustment information generated by the remote data processing platform is received to dynamically update the subsequent data processing process and transmission control strategy, forming a feedback optimization mechanism for the transmission strategy. This improves the utilization rate of communication resources while ensuring the reliability of key data transmission, achieving a synergistic improvement in the data transmission efficiency and reliability of the smartwatch.

[0022] It should be noted that the executing entity of the method in this embodiment can be a computing service device with data processing, network communication, and program execution functions, or it can be the aforementioned smartwatch with the same or similar functions. This embodiment and the following embodiments will be described using a smartwatch as an example.

[0023] Based on this, a first embodiment of the smartwatch data transmission method of this application is proposed. Please refer to... Figure 1 , Figure 1 This is a flowchart illustrating the first embodiment of the smartwatch data transmission method of this application.

[0024] In this embodiment, the method is applied to a data transmission system consisting of a smartwatch terminal, a remote data processing platform, and a communication network. The smartwatch data transmission method includes the following steps: S1: Acquire multi-source physiological monitoring data collected by the smartwatch terminal, and process the multi-source physiological monitoring data to generate a data object to be transmitted; S2: Perform terminal-side status recognition processing based on the data object to be transmitted to determine the data status identifier corresponding to the data object to be transmitted; It should be noted that multi-source physiological monitoring data refers to a set of data related to the user's physiological state collected by different types of sensor units built into the smartwatch terminal, including but not limited to heart rate information, exercise status information, blood oxygen related information, body surface status information, and composite monitoring data formed by the fusion of multiple sensor signals. Data processing refers to the process of preprocessing and structuring the raw physiological monitoring data collected on the smartwatch terminal side. The data object to be transmitted refers to the data unit formed after data processing, which has a unified data structure and can be directly called by the transmission module. Terminal-side status recognition processing refers to the process of analyzing and judging the data object to be transmitted locally on the smartwatch terminal. Data status identifier refers to the marking information used to characterize the attribute characteristics of the data object to be transmitted.

[0025] Specifically, the smartwatch continuously collects monitoring signals from multiple physiological sensor modules during operation. Due to differences in data acquisition cycles, data formats, and data stability among these modules, the terminal first performs unified processing on the collected multi-source physiological monitoring data. This includes aligning data from different sources along a time dimension, enabling correlation between data from different sampling periods under a unified time benchmark; simultaneously, filtering or correcting abnormal fluctuations; and structuring data fields according to preset data organization rules. After completing the data standardization process, the terminal encapsulates multiple physiological parameters according to a unified data description structure, forming data units with complete contextual information. This generates data objects that can be directly called by subsequent modules, transforming the original discrete monitoring data into a data foundation with a consistent expression format.

[0026] Furthermore, after generating the data object to be transmitted, the smartwatch terminal performs terminal-side state recognition processing based on the data content and its changing characteristics contained within the data object. The terminal analyzes the physiological parameter combinations, changing trend information, and data completeness within the data object to determine the current data's state category. Based on preset state determination rules or models, the terminal classifies and identifies the data object to be transmitted, mapping the identification results to corresponding data state identifiers. This ensures that each data object to be transmitted is associated with a clear state label, thereby completing the determination of the data state identifier corresponding to the data object to be transmitted.

[0027] This step first converts multi-source heterogeneous physiological monitoring data into a uniformly structured data object to be transmitted. Then, the terminal side identifies the status of this data object and generates a data status identifier. This ensures that the data has status information that can characterize its transmission needs before entering the transmission stage, thus avoiding the use of a uniform transmission method for all data. At the same time, by completing the status determination locally on the terminal, the real-time dependence on the remote platform is reduced, allowing subsequent transmission control to be directly scheduled based on the data status. This achieves a pre-linkage between data organization and transmission decision-making, providing a foundation for improving the efficiency and stability of data transmission.

[0028] S3: Determine the transmission control strategy corresponding to the data object to be transmitted based on the data status identifier and the current communication environment information; S4: Based on the transmission control strategy, encapsulate the data object to be transmitted and send it to the remote data processing platform; It should be noted that communication environment information refers to the network status parameters related to data transmission obtained by the smartwatch terminal at the current moment. Transmission control strategy refers to the set of data transmission rules determined based on data status identifiers and communication environment information. Encapsulation refers to the process of structuring and organizing the data to be transmitted according to a preset data communication format. The remote data processing platform refers to the backend processing system that establishes a data interaction connection with the smartwatch terminal through the communication network.

[0029] Specifically, after determining the data status identifier, the smartwatch terminal further acquires the current communication network's operational status information to form communication environment information. Because wearable devices experience dynamic changes in network conditions during mobile scenarios, and the appropriate data transmission methods differ under different communication states, the terminal performs correlation analysis between the data status identifier and the communication environment information. Based on preset policy matching rules, the terminal jointly judges the data attributes reflected by the data status identifier and the network conditions reflected by the communication environment information, selecting a transmission control policy from the policy set that matches the current conditions, or generating corresponding policy parameters based on the matching result, thereby determining the transmission control policy corresponding to the data object to be transmitted.

[0030] Furthermore, after determining the transmission control strategy, the smartwatch terminal performs data organization processing on the data object to be transmitted according to the transmission control strategy. The terminal performs structured encapsulation of the data object to be transmitted according to the data organization method defined in the strategy. During the encapsulation process, necessary control information is associated with the data content, ensuring that the encapsulated data unit meets the requirements of network transmission and platform parsing. Subsequently, the terminal sends the encapsulated data to the remote data processing platform through the communication network according to the transmission control rules specified in the transmission control strategy. During the transmission process, the terminal executes transmission scheduling or transmission control according to the strategy requirements, enabling the data object to be transmitted to complete its transmission to the remote data processing platform.

[0031] This step involves jointly analyzing data status identifiers and communication environment information to determine the transmission control strategy. This allows the data transmission method to be dynamically matched based on both data attributes and network conditions, avoiding the use of a fixed transmission mechanism under different communication states. Furthermore, by specifically encapsulating and sending the data objects to be transmitted according to the transmission control strategy, the data organization method and transmission behavior are consistently controlled, thereby reducing the communication load and transmission failure risk caused by incompatible transmission. This achieves adaptive scheduling of the data transmission process, improving the data transmission efficiency and reliability of smartwatches in complex communication environments.

[0032] S5: Receive the strategy adjustment information generated by the remote data processing platform, and update the subsequent data processing process of the data object to be transmitted and the transmission control strategy according to the strategy adjustment information.

[0033] It should be noted that strategy adjustment information refers to control information generated by the remote data processing platform based on the received data's operational status, processing results, or system operation. The data processing process refers to the processing flow performed by the smartwatch terminal on the collected multi-source physiological monitoring data before generating the data object to be transmitted. The data object to be transmitted refers to the data unit formed after data processing on the terminal side, used for subsequent status identification and data transmission.

[0034] Specifically, after the smartwatch sends the data to be transmitted to the remote data processing platform, the platform analyzes and processes the received data, generating policy adjustment information corresponding to the current system operating status. This policy adjustment information is returned to the smartwatch via the communication network. Upon receiving the policy adjustment information, the smartwatch parses it to identify the adjustment instructions and extract parameters related to the data processing and transmission control strategies. The smartwatch then performs structured parsing of the policy adjustment information, converting external feedback into update criteria that can be used by the local control module.

[0035] Furthermore, after parsing the strategy adjustment information, the smartwatch terminal adjusts the data processing procedures for the data objects to be generated and transmitted, based on the strategy adjustment information. This includes changing the data organization method or adjusting the data processing rules to ensure that the generated data objects meet the new processing requirements. Simultaneously, the terminal updates the currently used transmission control strategy based on the strategy adjustment information, ensuring that the data objects to be transmitted are encapsulated and transmitted according to the updated transmission rules during the transmission process.

[0036] This step involves receiving policy adjustment information generated by a remote data processing platform and using this information to update the data processing process and transmission control policy on the terminal side. This enables the data transmission system to form a feedback adjustment mechanism based on actual operating conditions, allowing the generation and transmission methods of subsequent data objects to be transmitted to be dynamically adjusted according to the system status. By introducing the remote platform to participate in policy optimization and perform updates on the terminal side, transmission control no longer relies on fixed rules but can continuously adapt to changes in data and communication conditions. This improves the stability and adaptability of the data transmission process and further enhances the overall reliability and continuous operation capability of data transmission.

[0037] This embodiment acquires multi-source physiological monitoring data collected by a smartwatch terminal, processes the multi-source physiological monitoring data to generate a data object to be transmitted; performs terminal-side state recognition processing based on the data object to be transmitted to determine the data status identifier corresponding to the data object to be transmitted; determines the transmission control strategy corresponding to the data object to be transmitted based on the data status identifier and the current communication environment information; encapsulates the data object to be transmitted based on the transmission control strategy and sends it to a remote data processing platform; receives strategy adjustment information generated by the remote data processing platform, and updates the subsequent data processing process and transmission control strategy of the data object to be transmitted according to the strategy adjustment information. This embodiment generates a data object to be transmitted by processing multi-source physiological monitoring data collected by the smartwatch terminal. Based on the data object, the terminal-side status is identified to determine the data status identifier. Then, the corresponding transmission control strategy is determined by combining the data status identifier with the current communication environment information, so that the data transmission process can be adaptively adjusted according to data characteristics and communication conditions. At the same time, the data object to be transmitted is encapsulated and sent based on the transmission control strategy, and the strategy adjustment information generated by the remote data processing platform is received to dynamically update the subsequent data processing process and transmission control strategy, forming a feedback optimization mechanism for the transmission strategy. This improves the utilization rate of communication resources while ensuring the reliability of key data transmission, and achieves a synergistic improvement in the data transmission efficiency and reliability of the smartwatch.

[0038] Based on the first embodiment described above, a second embodiment of the smartwatch data transmission method of this application is proposed. Please refer to... Figure 2 , Figure 2 This is a schematic diagram of a sub-process in the second embodiment of the smartwatch data transmission method of this application.

[0039] like Figure 2 As shown, in this embodiment, step S1 includes: S11: Acquire multi-source physiological monitoring data collected by the smartwatch terminal, and perform signal preprocessing on the multi-source physiological monitoring data to obtain preprocessed physiological data after removing interference components; S12: Based on the preprocessed physiological data, perform feature extraction processing to obtain a set of feature parameters; S13: Perform data compression and structured encapsulation on the set of feature parameters to generate the data object to be transmitted.

[0040] It should be noted that signal preprocessing refers to the process of performing basic signal processing operations on raw physiological monitoring data before it enters subsequent analysis. Interference components refer to non-target signal components introduced due to factors such as environmental changes, human movement, changes in sensor contact status, or equipment noise. Preprocessed physiological data refers to physiological monitoring data that has undergone signal preprocessing, after which interference components have been removed or suppressed, resulting in higher stability. Feature extraction processing refers to the process of extracting data parameters that characterize the patterns of physiological state changes from the preprocessed physiological data. Structured encapsulation refers to the process of organizing data into fields and constructing data units according to a preset data organization format.

[0041] Specifically, during operation, the smartwatch continuously collects monitoring signals from multiple physiological sensing modules. Because wearable devices are easily affected by human movement, environmental changes, and fluctuations in sensor contact during actual use, the raw data typically contains various types of interference components. Therefore, the terminal first performs signal preprocessing on the multi-source physiological monitoring data. By performing stability correction, abnormal fluctuation suppression, and signal uniformity processing, preprocessed physiological data with interference components removed is obtained. After obtaining the preprocessed physiological data, the terminal performs feature extraction processing, converting the continuously changing physiological signals into parameter information that reflects the characteristics of data changes. By analyzing data trends, change patterns, and data distribution characteristics, multiple feature parameters are extracted and organized into a feature parameter set, transforming the original high-dimensional signal into a computable and comparable data expression.

[0042] Furthermore, after forming the feature parameter set, the smartwatch terminal performs data compression processing on the set to reduce redundant expressions in the data and adapt the data size to the communication resource limitations of the wearable device. During compression, the correlation between key feature parameters is preserved, ensuring the data still fully expresses the monitoring status. Subsequently, the terminal, according to preset data organization rules, structurally encapsulates the compressed feature parameter set, uniformly organizing the feature parameters and necessary descriptive information to generate data units with standard data structures, thereby forming the data object to be transmitted and providing a unified input basis for subsequent status recognition and transmission control.

[0043] This step, by sequentially performing signal preprocessing, feature extraction, and data compression and structured encapsulation on multi-source physiological monitoring data, transforms the original, easily interfered, and large-volume monitoring signals into stable and structurally uniform data objects to be transmitted. This achieves data quality optimization and data scale control before entering the transmission stage. By reducing interference data and data redundancy while preserving key feature information, the communication resources required for subsequent data transmission are effectively controlled, and the impact of abnormal data on the transmission process is reduced. This provides a foundation for improving the efficiency and stability of smartwatch data transmission.

[0044] Based on the first embodiment described above, in this embodiment, step S2 includes: S21: Perform data parsing on the data object to be transmitted, extract physiological feature information, time correlation information and data source identification information, and construct a feature input dataset for state determination; S22: Input the feature input dataset into a preset recognition model for state reasoning processing to obtain a state determination result corresponding to the data object to be transmitted, wherein the state reasoning processing is based on the combined relationship between the physiological feature information and the time-related information. S23: Generate a data status identifier associated with the data object to be transmitted based on the status determination result.

[0045] It should be noted that physiological characteristic information refers to parameter information extracted from physiological monitoring data, used to characterize the user's current physiological state or trend of change. Time-related information refers to information reflecting the data collection time sequence, time interval, or historical correlation. Data source identification information refers to information used to mark the data source channel or acquisition module. Pre-set recognition model refers to a state recognition model pre-deployed in the smartwatch terminal or its processing module.

[0046] Specifically, after generating the data object to be transmitted, the smartwatch terminal first performs data parsing processing on the data object. According to preset data structure rules, the terminal breaks down and reads different fields in the data object, extracting physiological characteristic information, time-related information, and data source identification information. Physiological characteristic information reflects the state characteristics of the monitored data, time-related information describes the changes in the data over time, and data source identification information distinguishes the attributes of data from different monitoring sources. The terminal integrates these multiple types of information according to a unified data organization method, establishing a feature input dataset containing multi-dimensional descriptive information. This ensures that the input data not only includes current physiological state characteristics but also time context information and source information, thus constructing a complete input foundation for state determination.

[0047] Furthermore, after forming the feature input dataset, the smartwatch terminal inputs this dataset into a preset recognition model to perform state reasoning processing. The recognition model analyzes the combined relationship between physiological feature information and time-related information, and outputs the corresponding state determination result by comprehensively judging the data change trend and time-related pattern. Subsequently, the terminal generates a data state identifier associated with the data object to be transmitted based on the state determination result, and writes or binds this identifier to the data object to be transmitted, so that the data object has a clear state attribute.

[0048] This step parses the data objects to be transmitted and constructs a feature input dataset containing physiological characteristics, temporal correlation information, and data source identification information. This allows state determination to be based not only on a single data value but also on reasoning based on the combination of multi-dimensional information. Furthermore, a preset recognition model is used to perform state reasoning processing and generate data state labels. This ensures that each data object has a label that can characterize its state attributes before transmission, thus providing a clear basis for subsequent transmission control strategies. This avoids resource waste or transmission instability problems caused by a unified transmission processing method, thereby improving the pertinence of data transmission decisions and the reliability of the overall transmission process.

[0049] This embodiment acquires multi-source physiological monitoring data collected by a smartwatch terminal, processes the multi-source physiological monitoring data to generate a data object to be transmitted; performs terminal-side state recognition processing based on the data object to be transmitted to determine the data status identifier corresponding to the data object to be transmitted; determines the transmission control strategy corresponding to the data object to be transmitted based on the data status identifier and the current communication environment information; encapsulates the data object to be transmitted based on the transmission control strategy and sends it to a remote data processing platform; receives strategy adjustment information generated by the remote data processing platform, and updates the subsequent data processing process and transmission control strategy of the data object to be transmitted according to the strategy adjustment information. This embodiment generates a data object to be transmitted by processing multi-source physiological monitoring data collected by the smartwatch terminal. Based on the data object, the terminal-side status is identified to determine the data status identifier. Then, the corresponding transmission control strategy is determined by combining the data status identifier with the current communication environment information, so that the data transmission process can be adaptively adjusted according to data characteristics and communication conditions. At the same time, the data object to be transmitted is encapsulated and sent based on the transmission control strategy, and the strategy adjustment information generated by the remote data processing platform is received to dynamically update the subsequent data processing process and transmission control strategy, forming a feedback optimization mechanism for the transmission strategy. This improves the utilization rate of communication resources while ensuring the reliability of key data transmission, and achieves a synergistic improvement in the data transmission efficiency and reliability of the smartwatch.

[0050] Based on the second embodiment described above, a third embodiment of the smartwatch data transmission method of this application is proposed. Please refer to... Figure 3 , Figure 3 This is a schematic diagram of a sub-process in the third embodiment of the smartwatch data transmission method of this application.

[0051] In this embodiment, step S3 includes: S31: Obtain communication environment information related to the transmission process of the data object to be transmitted, and perform state characterization processing on the communication environment information to obtain a set of communication environment parameters; S32: Perform strategy matching processing based on the data status identifier and the communication environment parameter set to determine candidate transmission strategies from a preset transmission strategy set, wherein the candidate transmission strategies include control parameters related to transmission path selection and data protection methods; S33: Perform strategy determination processing on the candidate transmission strategy to generate a transmission control strategy associated with the data object to be transmitted.

[0052] It should be noted that communication environment information refers to information acquired by the smartwatch terminal during data transmission that reflects the current operating status of the communication network, including network connection status, signal stability, link quality, and communication resource usage. State characterization processing refers to the process of organizing and parameterizing the communication environment information. Policy matching processing refers to the process of filtering or associating preset policies based on data state identifiers and a set of communication environment parameters. The preset transmission policy set refers to a set of multiple transmission policies pre-configured by the system, each policy corresponding to different communication conditions or data state scenarios. Transmission path selection refers to the control method that determines which communication link or network method the data will be transmitted through. Data protection methods refer to the processing methods used to ensure data integrity and security during data transmission. Transmission control policy refers to the final determined policy rules used to control the transmission behavior of the data object to be transmitted.

[0053] Specifically, before the data to be transmitted enters the transmission phase, the smartwatch terminal first acquires communication environment information related to the current data transmission process. Because communication conditions for wearable devices continuously change in mobile scenarios, the original communication information typically presents as multi-dimensional state data. Therefore, the terminal performs state characterization processing on the communication environment information, converting discrete network state descriptions into a unified parameter expression form, thereby forming a communication environment parameter set to characterize the current communication environment features. Subsequently, the terminal jointly analyzes the communication environment parameter set and data state identifiers, and through strategy matching processing, filters strategy items that match the current data attributes and communication conditions from a preset transmission strategy set to obtain candidate transmission strategies. These candidate transmission strategies include control parameters related to transmission path selection and data protection methods, ensuring that strategy selection considers both data importance and network status.

[0054] Furthermore, after obtaining candidate transmission strategies, the smartwatch terminal performs a strategy determination process. Based on preset strategy selection rules, the terminal compares and confirms multiple candidate strategies to determine the most suitable strategy configuration for the current data object to be transmitted. During the strategy determination process, the terminal associates and binds the finally determined control parameters with the data object to be transmitted, enabling the data object to perform transmission operations according to the corresponding control rules in subsequent transmission phases, thereby generating a transmission control strategy associated with the data object to be transmitted.

[0055] This step involves forming a set of communication environment parameters by performing state characterization processing on the communication environment information, and then performing joint policy matching with the data state identifier. This allows the determination of the transmission strategy to be based on both data attributes and network status. Furthermore, by selecting candidate strategies from the preset transmission strategy set and generating the final transmission control strategy, data in different states can adopt differentiated transmission methods in different communication environments. This avoids resource waste or transmission instability caused by fixed transmission modes, and enables adaptive selection of data transmission paths and protection methods, thereby improving the stability of the data transmission process and the efficiency of communication resource utilization.

[0056] Based on the second embodiment described above, in this embodiment, step S4 includes: S41: Based on the transmission control strategy, determine the data encapsulation parameters corresponding to the data object to be transmitted, and perform structured encapsulation processing on the data object to be transmitted based on the data encapsulation parameters to generate a data packet to be sent. S42: Based on the transmission control strategy, perform transmission configuration processing on the data packet to be sent to determine the corresponding transmission path information and data protection parameters, and obtain the target data to be sent; S43: Based on the transmission path information, the target data is sent to the remote data processing platform through the communication network.

[0057] It should be noted that data encapsulation parameters refer to data organization parameters determined according to the transmission control strategy. Transmission configuration processing refers to the process of configuring relevant parameters for the data packet to be sent according to the transmission control strategy. Transmission path information refers to information indicating which communication link or network method the data will be sent through. Data protection parameters refer to control parameters used to ensure data integrity or consistency during data transmission. Target data to be sent refers to the data content that is ready to be sent after the transmission configuration processing is completed. Communication network refers to the communication system used to realize data interaction between the smartwatch terminal and the remote data processing platform. Remote data processing platform refers to the backend system that receives data sent by the smartwatch terminal and performs subsequent processing.

[0058] Specifically, after determining the transmission control strategy, the smartwatch terminal first determines the data encapsulation parameters corresponding to the data object to be transmitted based on this strategy. Since different data states and communication conditions require different data organization methods, the terminal determines the data field arrangement, control information organization, and encapsulation structure configuration according to the control rules specified in the transmission control strategy. Subsequently, the terminal performs structured encapsulation processing on the data object to be transmitted based on the data encapsulation parameters, uniformly organizing the data content and necessary control information to generate a data packet to be sent. This data packet forms a unified data structure, enabling the data to be stably transmitted over the communication network and correctly parsed by the remote data processing platform.

[0059] Furthermore, after generating the data packet to be sent, the smartwatch terminal performs transmission configuration processing on the data packet according to the transmission control policy. The terminal determines the corresponding transmission path information and data protection parameters according to the policy requirements, ensuring that the data transmission method matches the current communication conditions. After configuration, the terminal converts the data packet to be sent into target transmission data and, based on the transmission path information, sends the target transmission data to the remote data processing platform via the communication network, thereby completing the data transmission process corresponding to the data object to be transmitted.

[0060] Because this step coordinates the data encapsulation and transmission methods based on the transmission control strategy, the data is structured and configured with transmission parameters according to the current strategy before transmission, thus avoiding the incompatibility issues caused by uniform encapsulation or fixed transmission methods. By first generating data packets that meet the strategy requirements and then executing transmission based on the transmission path information and data protection parameters, a consistent control relationship is formed between the data organization process and the transmission process, thereby improving the transmission stability and reliability of data in different communication environments and improving the efficiency of communication resource utilization.

[0061] Based on the second embodiment described above, in this embodiment, step S5 includes: S51: Receive the strategy adjustment information sent by the remote data processing platform, and parse the strategy adjustment information to obtain a set of adjustment parameters related to the data processing rules and transmission control rules; S52: Based on the set of adjustment parameters, perform parameter update processing on the current terminal-side configuration to generate updated data processing parameters and updated transmission control parameters; S53: Adjust the data processing procedure of the subsequent data objects to be transmitted based on the updated data processing parameters, and update the transmission control strategy corresponding to the subsequent data objects to be transmitted based on the updated transmission control parameters.

[0062] It should be noted that "strategy adjustment information" refers to control information generated and sent to the terminal by the remote data processing platform based on system operating status or data analysis results. "Adjustment parameter set" refers to the set of parameters extracted from the strategy adjustment information, used to represent the data processing rules and transmission control rules that need to be adjusted. "Terminal-side configuration" refers to the configuration status of the data processing parameters and transmission control-related parameters used by the smartwatch terminal during its current operation.

[0063] Specifically, after the smartwatch terminal completes data transmission, the remote data processing platform generates strategy adjustment information based on the received data's operational status and sends it to the terminal via the communication network. Upon receiving the strategy adjustment information, the terminal first performs parsing processing, breaking down and identifying its data structure to extract control content related to system operation adjustments. During parsing, the terminal categorizes different control fields in the strategy adjustment information, identifying adjustment parameters related to data processing rules and transmission control rules, and organizes them into a unified adjustment parameter set, enabling external feedback information to be directly accessed by the terminal-side control module.

[0064] Furthermore, after obtaining the set of adjustment parameters, the smartwatch terminal performs parameter update processing on the current terminal-side configuration based on this set, replacing or correcting the original data processing parameters and transmission control parameters to generate updated data processing parameters and updated transmission control parameters. Subsequently, the terminal applies the updated data processing parameters to the data processing of subsequent data objects to be transmitted, ensuring that the subsequently generated data objects are constructed according to the new processing rules; simultaneously, it updates the transmission control strategy corresponding to the subsequent data objects to be transmitted based on the updated transmission control parameters, ensuring that subsequent data transmission behavior is executed according to the new control rules, thereby completing the dynamic adjustment of the system operation strategy.

[0065] This step involves receiving and parsing policy adjustment information sent by the remote data processing platform to extract a set of adjustment parameters to update the data processing and transmission control parameters on the terminal side. This allows the terminal's data processing and transmission methods to be dynamically adjusted based on actual operating conditions. By directly applying the updated parameters to the generation process and transmission control strategy of subsequent data objects to be transmitted, the system forms an adaptive adjustment mechanism based on feedback information. This avoids the compatibility degradation caused by long-term use of fixed processing and transmission rules, improves the adaptability of data transmission to environmental and business changes, and enhances the overall stability and continuous reliability of data transmission.

[0066] This embodiment acquires multi-source physiological monitoring data collected by a smartwatch terminal, processes the multi-source physiological monitoring data to generate a data object to be transmitted; performs terminal-side state recognition processing based on the data object to be transmitted to determine the data status identifier corresponding to the data object to be transmitted; determines the transmission control strategy corresponding to the data object to be transmitted based on the data status identifier and the current communication environment information; encapsulates the data object to be transmitted based on the transmission control strategy and sends it to a remote data processing platform; receives strategy adjustment information generated by the remote data processing platform, and updates the subsequent data processing process and transmission control strategy of the data object to be transmitted according to the strategy adjustment information. This embodiment generates a data object to be transmitted by processing multi-source physiological monitoring data collected by the smartwatch terminal. Based on the data object, the terminal-side status is identified to determine the data status identifier. Then, the corresponding transmission control strategy is determined by combining the data status identifier with the current communication environment information, so that the data transmission process can be adaptively adjusted according to data characteristics and communication conditions. At the same time, the data object to be transmitted is encapsulated and sent based on the transmission control strategy, and the strategy adjustment information generated by the remote data processing platform is received to dynamically update the subsequent data processing process and transmission control strategy, forming a feedback optimization mechanism for the transmission strategy. This improves the utilization rate of communication resources while ensuring the reliability of key data transmission, and achieves a synergistic improvement in the data transmission efficiency and reliability of the smartwatch.

[0067] In one embodiment, during the data processing and data transmission process performed by the smartwatch terminal, a data transmission context caching mechanism is further introduced to establish historical transmission context information related to the data object to be transmitted on the terminal side, and to assist in adjusting the transmission behavior of the current data object to be transmitted based on the historical transmission context information.

[0068] Specifically, after generating the data object to be transmitted and completing data status identification, the smartwatch terminal not only records the current data status identifier, but also associates and stores the historical transmission records, historical communication environment status, and historical transmission strategy execution results corresponding to the data object to be transmitted, thereby forming transmission context cache data. The transmission context cache data is used to describe the continuous transmission behavior characteristics of the data object over a period of time.

[0069] During subsequent data transmission, when the terminal determines the transmission control strategy based on the current data status identifier and communication environment information, the terminal further reads the transmission context cache data and performs consistency verification on the current strategy matching result. When a significant deviation is detected between the current strategy and historical continuous transmission behavior, the terminal performs a smooth adjustment process on the transmission control strategy to avoid frequent switching of transmission paths or frequent adjustments to data protection methods within a short period of time.

[0070] Furthermore, after the remote data processing platform returns the policy adjustment information, the terminal not only updates the current data processing parameters and transmission control parameters, but also writes the update results into the transmission context cache data, so that the subsequent policy determination process can simultaneously refer to the historical policy evolution process, thereby forming a transmission decision basis with time continuity.

[0071] Through the above implementation methods, the terminal side introduces a context-aware mechanism based on historical behavior on the basis of the original data state recognition and policy control. This enables the data transmission process to maintain the continuity and stability of policy changes in a dynamic environment, reduces frequent policy switching caused by instantaneous communication environment fluctuations, and provides a more stable execution foundation for the continuous data transmission of smartwatches in mobile scenarios.

[0072] This application also provides a smartwatch data transmission device; please refer to... Figure 4 , Figure 4 This is a schematic diagram of the module structure of a smartwatch data transmission device according to an embodiment of this application. The device is applied to a data transmission system consisting of a smartwatch terminal, a remote data processing platform, and a communication network. The smartwatch data transmission device includes: The monitoring data processing module 401 is used to acquire multi-source physiological monitoring data collected by the smartwatch terminal, and to process the multi-source physiological monitoring data to generate a data object to be transmitted. The status identification module 402 is used to perform terminal-side status identification processing based on the data object to be transmitted, and to determine the data status identifier corresponding to the data object to be transmitted. The transmission control module 403 is used to determine the transmission control strategy corresponding to the data object to be transmitted based on the data status identifier and the current communication environment information. The encapsulation and transmission module 404 is used to encapsulate the data object to be transmitted based on the transmission control strategy and send it to the remote data processing platform. The target module 405 is used to receive the strategy adjustment information generated by the remote data processing platform, and update the subsequent data processing process of the data object to be transmitted and the transmission control strategy according to the strategy adjustment information.

[0073] The smartwatch data transmission device provided in this application, employing the smartwatch data transmission method described in the above embodiments, can solve the technical problem of how to improve the efficiency and reliability of smartwatch data transmission. Compared with the prior art, the beneficial effects of the smartwatch data transmission device provided in this application are the same as those of the smartwatch data transmission method provided in the above embodiments, and other technical features in the smartwatch data transmission device are the same as those disclosed in the methods of the above embodiments, and will not be repeated here.

[0074] This application provides a smartwatch, which includes: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, which are executed by the at least one processor to enable the at least one processor to perform the smartwatch data transmission method described in the above embodiments.

[0075] The following is for reference. Figure 5 , Figure 5 This is a schematic diagram of the hardware operating environment involved in the smartwatch data transmission method in the embodiments of this application, showing a schematic diagram of the structure of a smartwatch suitable for implementing the embodiments of this application. Figure 5 The smartwatch shown is merely an example and should not be construed as limiting the functionality and scope of use of the embodiments of this application.

[0076] like Figure 5 As shown, a smartwatch may include a processing unit 1001 (e.g., a central processing unit, a graphics processor, etc.), which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 1002 or a program loaded from a storage device 1003 into a random access memory (RAM) 1004. The RAM 1004 also stores various programs and data required for the operation of the smartwatch. The processing unit 1001, ROM 1002, and RAM 1004 are interconnected via a bus 1005. An input / output (I / O) interface 1006 is also connected to the bus. Typically, the following systems can be connected to the I / O interface 1006: input devices 1007 including, for example, a touchscreen, touchpad, keyboard, mouse, image sensor, microphone, accelerometer, gyroscope, etc.; output devices 1008 including, for example, a liquid crystal display (LCD), speaker, vibrator, etc.; storage devices 1003 including, for example, magnetic tape, hard disk, etc.; and communication devices 1009. The communication device 1009 allows the smartwatch to communicate wirelessly or wiredly with other devices to exchange data. While the figures show smartwatches with various systems, it should be understood that implementing or having all of the systems shown is not required. More or fewer systems may be implemented alternatively.

[0077] In particular, according to the embodiments disclosed in this application, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, the embodiments disclosed in this application include a computer program product comprising a computer program carried on a computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. When the computer program is executed by the processing device 1001, it performs the functions defined in the methods of the embodiments disclosed in this application.

[0078] The smartwatch provided in this application, employing the smartwatch data transmission method described in the above embodiments, can solve the technical problem of how to improve the efficiency and reliability of smartwatch data transmission. Compared with the prior art, the beneficial effects of the smartwatch provided in this application are the same as those of the smartwatch data transmission method provided in the above embodiments, and other technical features of this smartwatch are the same as those disclosed in the previous embodiment method, and will not be repeated here.

[0079] It should be understood that the various parts disclosed in this application can be implemented using hardware, software, firmware, or a combination thereof. In the description of the above embodiments, specific features, structures, materials, or characteristics can be combined in any suitable manner in one or more embodiments or examples.

[0080] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

[0081] This application provides a computer-readable storage medium having computer-readable program instructions (i.e., a computer program) stored thereon, which are used to execute the smartwatch data transmission method in the above embodiments.

[0082] The aforementioned computer-readable storage medium carries one or more programs. When these programs are executed by a smartwatch, the smartwatch causes the following: it acquires multi-source physiological monitoring data collected by the smartwatch terminal and processes the multi-source physiological monitoring data to generate a data object to be transmitted; it performs terminal-side state recognition processing based on the data object to be transmitted to determine the data status identifier corresponding to the data object; it determines the transmission control strategy corresponding to the data object to be transmitted based on the data status identifier and the current communication environment information; it encapsulates the data object to be transmitted based on the transmission control strategy and sends it to a remote data processing platform; it receives strategy adjustment information generated by the remote data processing platform and updates the subsequent data processing process and transmission control strategy of the data object to be transmitted based on the strategy adjustment information. Computer program code for performing the operations of this application can be written in one or more programming languages ​​or a combination thereof. These programming languages ​​include object-oriented programming languages—such as Java, Smalltalk, and C++—and conventional procedural programming languages—such as the "C" language or similar programming languages. The program code can execute entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network—including a local area network (LAN) or a wide area network (WAN)—or it can be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0083] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this application. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0084] The modules described in the embodiments of this application can be implemented in software or hardware. The names of the modules do not necessarily limit the functionality of the unit itself.

[0085] The readable storage medium provided in this application is a computer-readable storage medium that stores computer-readable program instructions (i.e., a computer program) for executing the above-described smartwatch data transmission method, thereby solving the technical problem of how to improve the efficiency and reliability of smartwatch data transmission. Compared with the prior art, the beneficial effects of the computer-readable storage medium provided in this application are the same as those of the smartwatch data transmission method provided in the above embodiments, and will not be repeated here.

[0086] This application provides a computer program product, including a computer program that, when executed by a processor, implements the steps of the smartwatch data transmission method described above.

[0087] The computer program product provided in this application can solve the technical problem of how to improve the efficiency and reliability of data transmission in smartwatches. Compared with the prior art, the beneficial effects of the computer program product provided in this application are the same as the beneficial effects of the smartwatch data transmission method provided in the above embodiments, and will not be repeated here.

[0088] All user-related data involved in this application (such as multi-source physiological monitoring data) were obtained with the user's permission or consent; that is, when this application is used in specific products or technologies, user permission is required to obtain and process the relevant data, and the processing of the relevant data must comply with the relevant laws, regulations and regulatory standards of the relevant countries and regions.

[0089] The above are merely preferred embodiments of this application and do not limit the patent scope of this application. Any equivalent structural or procedural transformations made using the content of this application's specification and drawings, or direct or indirect applications in other related technical fields, are similarly included within the patent scope of this application.

Claims

1. A data transmission method for a smartwatch, characterized in that, The method is applied to a data transmission system consisting of a smartwatch terminal, a remote data processing platform, and a communication network, characterized in that the method includes: Acquire multi-source physiological monitoring data collected by the smartwatch terminal, and process the multi-source physiological monitoring data to generate a data object to be transmitted; Based on the data object to be transmitted, perform terminal-side status recognition processing to determine the data status identifier corresponding to the data object to be transmitted. Based on the data status identifier and the current communication environment information, determine the transmission control strategy corresponding to the data object to be transmitted; The data object to be transmitted is encapsulated based on the transmission control strategy and sent to the remote data processing platform; The system receives policy adjustment information generated by the remote data processing platform and updates the subsequent data processing procedure for the data object to be transmitted and the transmission control policy based on the policy adjustment information.

2. The method as described in claim 1, characterized in that, The steps of acquiring multi-source physiological monitoring data collected by the smartwatch terminal and processing the multi-source physiological monitoring data to generate a data object to be transmitted include: Acquire multi-source physiological monitoring data collected by a smartwatch terminal, and perform signal preprocessing on the multi-source physiological monitoring data to obtain preprocessed physiological data after removing interference components; Based on the preprocessed physiological data, feature extraction processing is performed to obtain a set of feature parameters; The set of feature parameters is compressed and structured to generate the data object to be transmitted.

3. The method as described in claim 1, characterized in that, The step of performing terminal-side state recognition processing based on the data object to be transmitted, and determining the data state identifier corresponding to the data object to be transmitted, includes: The data object to be transmitted is parsed to extract physiological feature information, time correlation information and data source identification information, and a feature input dataset for state determination is constructed. The feature input dataset is input into a preset recognition model for state reasoning processing to obtain a state determination result corresponding to the data object to be transmitted. The state reasoning processing is based on the combined relationship between the physiological feature information and the time-related information. Based on the status determination result, a data status identifier associated with the data object to be transmitted is generated.

4. The method as described in claim 1, characterized in that, The step of determining the transmission control strategy corresponding to the data object to be transmitted based on the data status identifier and the current communication environment information includes: Obtain communication environment information related to the transmission process of the data object to be transmitted, and perform state characterization processing on the communication environment information to obtain a set of communication environment parameters; Based on the data status identifier and the communication environment parameter set, a strategy matching process is performed to determine candidate transmission strategies from a preset transmission strategy set, wherein the candidate transmission strategies include control parameters related to transmission path selection and data protection methods; The candidate transmission strategies are processed to determine the transmission control strategy associated with the data object to be transmitted.

5. The method as described in claim 1, characterized in that, The step of encapsulating the data object to be transmitted based on the transmission control strategy and sending it to the remote data processing platform includes: Based on the transmission control strategy, the data encapsulation parameters corresponding to the data object to be transmitted are determined, and the data object to be transmitted is subjected to structured encapsulation processing based on the data encapsulation parameters to generate a data packet to be sent. Based on the transmission control strategy, the data packet to be sent is processed for transmission configuration to determine the corresponding transmission path information and data protection parameters, thereby obtaining the target data to be sent. Based on the transmission path information, the target data is sent to the remote data processing platform through the communication network.

6. The method as described in claim 1, characterized in that, The step of receiving policy adjustment information generated by the remote data processing platform and updating the subsequent data processing procedure for the data object to be transmitted and the transmission control policy based on the policy adjustment information includes: The system receives policy adjustment information sent by the remote data processing platform and parses the policy adjustment information to obtain a set of adjustment parameters related to data processing rules and transmission control rules. Based on the set of adjustment parameters, the current terminal-side configuration is updated to generate updated data processing parameters and updated transmission control parameters. The data processing procedure for the subsequent data objects to be transmitted is adjusted based on the updated data processing parameters, and the transmission control strategy corresponding to the subsequent data objects to be transmitted is updated based on the updated transmission control parameters.

7. A data transmission device for a smartwatch, characterized in that, The device is applied to a data transmission system consisting of a smartwatch terminal, a remote data processing platform, and a communication network, and the device includes: The monitoring data processing module is used to acquire multi-source physiological monitoring data collected by the smartwatch terminal, and to process the multi-source physiological monitoring data to generate a data object to be transmitted. The status identification module is used to perform terminal-side status identification processing based on the data object to be transmitted, and to determine the data status identifier corresponding to the data object to be transmitted. The transmission control module is used to determine the transmission control strategy corresponding to the data object to be transmitted based on the data status identifier and the current communication environment information. An encapsulation and transmission module is used to encapsulate the data object to be transmitted based on the transmission control strategy and send it to the remote data processing platform. The target module is used to receive policy adjustment information generated by the remote data processing platform, and update the subsequent data processing process of the data object to be transmitted and the transmission control policy according to the policy adjustment information.

8. A smartwatch, characterized in that, The smartwatch includes: a memory, a processor, and a smartwatch data transmission program stored in the memory and executable on the processor, the smartwatch data transmission program being configured to implement the steps of the smartwatch data transmission method as described in any one of claims 1 to 6.

9. A storage medium, characterized in that, The storage medium stores a smartwatch data transmission program, which, when executed by a processor, implements the steps of the smartwatch data transmission method as described in any one of claims 1 to 6.

10. A computer program product, characterized in that, The computer program product includes a computer program that, when executed by a processor, implements the steps of the smartwatch data transmission method as described in any one of claims 1 to 6.

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