Communication control method and system based on smart wearable chip

Abstract

The invention relates to a communication control method and system based on a smart wearable chip, relates to the field of communication control, is applied to the smart wearable chip, and comprises the following steps: when a power management unit displays that a power supply is in a healthy state, receiving a first radio frequency signal through an RF processing unit for analysis, and obtaining a user communication instruction, the user communication instruction has a target communication data attribute and is sent to the application processor unit to carry out calculation power demand analysis, and expected calculation power is obtained; when the edge activation computing power is greater than or equal to the edge activation computing power threshold, configuring an edge computing power node, and combining a storage unit to obtain target communication data; and a second radio frequency signal is obtained and transmitted to the target user. The edge computing power node is used for mapping the target communication data which the storage unit does not have, mapping interaction of advanced semantics is achieved, and the technical effect of improving the intelligent degree of the wearable chip is achieved.

Description

Technical Field

[0001] The present invention relates to the field of communication control technology, and in particular to a communication control method and system based on a smart wearable chip. Background Art

[0002] In existing wearable chips, the communication control method mainly relies on the storage devices inside the chip to transmit existing data. When the user requires high-level semantic data, interactive communication is not possible. Furthermore, since the computing power of the wearable chip depends on local computing power, it is difficult to integrate processing logic with high computing power requirements.

[0003] In summary, current wearable chips rely on internal memory devices to transmit existing data, and are unable to achieve interaction between memory devices and data that is not already in the memory. Summary of the Invention

[0004] The present invention aims to solve the technical problem in the prior art that interaction without data in the memory cannot be achieved, resulting in a low level of intelligence, and provides a communication control method and system based on a smart wearable chip to solve the problem.

[0005] The technical solution of the present invention to solve the above technical problems is as follows:

[0006] In the first aspect, the present invention provides a communication control method based on a smart wearable chip, which is applied to a communication control system based on a smart wearable chip. The system is deployed on the smart wearable chip, and the smart wearable chip includes a power management unit, an application processor unit, a storage unit and a wireless communication unit. The wireless communication unit includes an RF processing unit, including: when the power management unit indicates that it is in a healthy power state, the first radio frequency signal is received by the RF processing unit for analysis to obtain a user communication instruction, wherein the user communication instruction has a target communication data attribute; when the target communication data attribute does not exist in the storage unit, the target communication data attribute is sent to the application processor unit for computing power demand analysis to obtain the expected computing power; when the expected computing power is greater than or equal to the edge activation computing power threshold, an edge computing power node is configured; the edge computing power node is communicated with and connected to the target communication power node, and the target communication data attribute is generated in combination with the storage unit to obtain the target communication data; the target communication data is modulated by the RF processing unit to obtain a second radio frequency signal, and the second radio frequency signal is transmitted to the target user.

[0007] In the second aspect, the present invention provides a communication control system based on a smart wearable chip, which is applied to a communication control system based on a smart wearable chip. The system is deployed on the smart wearable chip, and the smart wearable chip includes a power management unit, an application processor unit, a storage unit and a wireless communication unit. The wireless communication unit includes an RF processing unit, including: a communication instruction parsing module, which is used to receive a first radio frequency signal through the RF processing unit for parsing when the power management unit indicates that the power is in a healthy state, and obtain a user communication instruction, wherein the user communication instruction has a target communication data attribute; a demand computing power parsing module, which is used to send the target communication data attribute to the application processor unit for computing power demand parsing when the target communication data attribute does not exist in the storage unit, and obtain the expected computing power; an edge node configuration module, which is used to configure an edge computing power node when the expected computing power is greater than or equal to the edge activation computing power threshold; a communication data generation module, which is used to communicate with the edge computing power node, generate the target communication data attribute in combination with the storage unit, and obtain the target communication data; a communication task execution module, which is used to modulate the target communication data through the RF processing unit to obtain a second radio frequency signal, and transmit the second radio frequency signal to the target user.

[0008] In a third aspect, the present invention provides an electronic device comprising: a memory for storing a computer software program; and a processor for reading and executing the computer software program, thereby implementing the communication control method based on the smart wearable chip described in the first aspect.

[0009] In a fourth aspect, the present invention provides a non-transitory computer-readable storage medium, in which a computer software program is stored. When the computer software program is executed by a processor, the communication control method based on the smart wearable chip described in the first aspect is implemented.

[0010] The beneficial effects of the present invention are as follows: when the power management unit indicates that the power is in a healthy state, the RF processing unit receives the first radio frequency signal for analysis to obtain a user communication instruction, wherein the user communication instruction has the target communication data attribute and is sent to the application processor unit for computing power demand analysis to obtain the expected computing power; when it is greater than or equal to the edge activation computing power threshold, the edge computing power node is configured and combined with the storage unit to obtain the target communication data; the RF processing unit is modulated to obtain a second radio frequency signal to transmit to the target user. By using the edge computing power node to map the target communication data that the storage unit does not have, high-level semantic mapping interaction is realized, achieving the technical effect of improving the intelligence level of the wearable chip. BRIEF DESCRIPTION OF THE DRAWINGS

[0011] Figure 1 A flow chart of the communication control method based on the smart wearable chip provided by the present invention;

[0012] Figure 2 This is a schematic diagram of the structure of the communication control system based on the smart wearable chip provided by the present invention;

[0013] Figure 3 A schematic structural diagram of the electronic device provided by the present invention;

[0014] Figure 4 A schematic structural diagram of a computer-readable storage medium provided by the present invention;

[0015] Figure 5 This is a schematic diagram of the structure of the smart wearable chip provided by the present invention.

[0016] In the accompanying drawings, the components represented by the reference numerals are described as follows:

[0017] Electronic device 500 , memory 510 , processor 520 , first computer program 511 , computer-readable storage medium 600 , second computer program 611 . DETAILED DESCRIPTION

[0018] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without making any creative efforts shall fall within the scope of protection of the present invention.

[0019] In the description of the present invention, the terms "first" and "second" are used for descriptive purposes only and should not be understood to indicate or imply relative importance or implicitly specify the number of the technical features indicated. Therefore, a feature specified as "first" or "second" may explicitly or implicitly include one or more of the specified features. In the description of the present invention, "plurality" means two or more, unless otherwise specifically defined.

[0020] In the description of the present invention, the term "for example" is used to mean "used as an example, illustration or illustration". Any embodiment of the present invention described as "for example" is not necessarily to be construed as being more preferred or advantageous than other embodiments. The following description is given to enable any person skilled in the art to implement and use the present invention. In the following description, details are listed for the purpose of explanation. It should be understood that a person of ordinary skill in the art can recognize that the present invention can be implemented without using these specific details. In other examples, well-known structures and processes are not elaborated in detail to avoid obscuring the description of the present invention with unnecessary details. Therefore, the present invention is not intended to be limited to the embodiments shown, but is consistent with the widest scope consistent with the principles and features disclosed herein.

[0021] Example 1:

[0022] like Figure 1 As shown, an embodiment of the present invention provides a communication control method based on a smart wearable chip, which is applied to a communication control system based on a smart wearable chip. The system is deployed on the smart wearable chip, and the smart wearable chip includes a power management unit, an application processor unit, a storage unit, and a wireless communication unit. The wireless communication unit includes an RF processing unit, including the following steps:

[0023] Specifically, if Figure 5 As shown, the smart wearable chip is a microchip integrated into the wearable chip, which has processing and storage capabilities and can realize interaction with users and data collection and transmission; the communication control system: refers to the system used to manage and control the communication functions of the smart wearable chip, which is responsible for handling the wireless communication tasks of the device, including signal reception, processing and transmission; the power management unit: is responsible for monitoring and managing the power status of the smart wearable chip to ensure that the device operates with sufficient and stable power; the application processor unit: is the computing core in the smart wearable chip, responsible for executing various applications and processing tasks; the storage unit: is used to store data of the smart wearable chip, including the operating system, applications and user data; the wireless communication unit: is responsible for the wireless communication functions of the smart wearable chip, including signal reception and transmission; the RF processing unit: is a part of the wireless communication unit, specifically responsible for processing radio frequency signals, including signal modulation, demodulation and other related tasks of wireless communication. The power management unit, the application processing unit, the storage unit, the wireless communication unit including the RF processing unit are integrated on the same wafer. Compared with traditional module integration solutions, it occupies less space and is smaller in size. At the same time, due to integration on the same wafer, the interaction is more efficient, ensuring the stability of subsequent communications.

[0024] S10: When the power management unit indicates that the power is in a healthy state, the RF processing unit receives and analyzes the first radio frequency signal to obtain a user communication instruction, wherein the user communication instruction has a target communication data attribute;

[0025] Specifically, the power management unit: This is the component in the smart wearable chip responsible for monitoring and managing the power status, ensuring that the device operates with sufficient and stable power; power health status: refers to the power parameters (such as voltage, current, power, etc.) monitored by the power management unit within the preset safe and effective range, allowing the device to operate normally; RF processing unit: that is, the radio frequency processing unit, responsible for receiving, sending and processing radio frequency signals in wireless communications; first radio frequency signal: refers to the signal sent from the outside to the smart wearable chip, usually containing the user's communication instructions; user communication instructions: instructions sent by the user to the wearable chip through wireless communication. These instructions guide the device to perform specific operations; target communication data attributes: refers to the data characteristics or attributes contained in the user communication instructions. These attributes define the goals and requirements of the communication data, such as data type, format, size, etc.

[0026] Specifically, within the communication control system of the smart wearable chip, the power management unit first checks the power status to ensure the device is in a healthy state. Once this is confirmed, the RF processing unit begins operating, receiving the first external RF signal. This signal contains the user's communication instructions, which the RF processing unit must parse to obtain.

[0027] After receiving the user's communication instruction, the system further extracts the target communication data attributes contained in the instruction. This step is crucial because it determines the direction of subsequent data processing and communication. Parsing the target communication data attributes is the bridge between user needs and device responses, ensuring that the device can understand and execute the user's high-level semantic data request.

[0028] S20: When the target communication data attribute does not exist in the storage unit, the target communication data attribute is sent to the application processor unit for computing power requirement analysis to obtain the expected computing power;

[0029] Specifically, the non-existence of the target communication data attribute means that no data attribute matching the received user communication instruction is found in the storage unit of the smart wearable chip, that is, the required data is not in the local storage; application processor unit: the component in the smart wearable chip responsible for performing complex data processing and computing tasks; computing power requirement analysis: refers to analyzing the computing resources required for processing the target communication data attributes to determine the computing power required to complete the task; expected computing power: based on the results of the computing power requirement analysis, determine the ideal or expected computing power required to complete the processing of the target communication data attributes.

[0030] When the required target communication data attributes do not exist in the smart wearable chip's storage unit, the system sends this request to the application processor unit for further processing. The application processor unit will analyze the computing power requirements of the target communication data attributes, which involves evaluating the computational complexity and resources required to process this data.

[0031] Specifically, the application processor unit may analyze factors such as the data type, size, and complexity of the processing algorithm to determine how much CPU cycles, memory bandwidth, or other computing resources are required to process the data. After the analysis is complete, the application processor unit will derive an expected computing power value, which represents the ideal computing power required to complete the processing of the target communication data attributes.

[0032] S30: When the expected computing power is greater than or equal to the edge activation computing power threshold, configure the edge computing power node;

[0033] Specifically, the edge activation computing power threshold is a preset performance parameter used to determine when additional computing resources are needed to process tasks. When the computing power required for the computing task reaches or exceeds this threshold, the system will consider the need to activate the edge computing power node; edge computing power nodes refer to computing resources deployed at the edge of the network, close to the data source or user. They can be local servers, cloud services, or devices with high computing power, which are used to provide the necessary computing power to process tasks that require a lot of computing power; configuring edge computing power nodes refers to the process of dynamically selecting and allocating edge computing power nodes based on computing needs to ensure that there are sufficient computing resources to process specific tasks.

[0034] If the smart wearable chip needs to process large amounts of data analysis or machine learning tasks that require computing resources beyond the device's capabilities, the system will automatically configure edge computing nodes to provide additional computing support. This allows the smart wearable chip to perform more advanced functions, such as real-time voice recognition, image processing, or complex data analysis, without sacrificing performance or user experience. In this way, the smart wearable chip can maintain its portability and functionality while leveraging the powerful capabilities of edge computing to expand its application range.

[0035] S40: Communicate with the edge computing node, generate the target communication data attributes in conjunction with the storage unit, and obtain the target communication data;

[0036] Specifically, the target communication data is actual data generated according to the target communication data attributes, and these data are the specific information requested by the user communication instruction.

[0037] After the smart wearable chip establishes a communication connection with the edge computing node, the system will process and generate the target communication data attributes in combination with the data in the storage unit to obtain the target communication data. The detailed process is as follows:

[0038] First, the system retrieves data related to the target communication data attributes from the storage unit, which may include the user's historical data, profiles, or other related information; then, the edge computing node processes the retrieved data to generate data that meets the requirements of the target communication data attributes, which may involve data aggregation, analysis, conversion, or execution of specific algorithms; then, based on the processing results, the system generates the target communication data, which may include creating new data structures, files, or information to meet the user's communication instructions.

[0039] S50: Modulate the target communication data through the RF processing unit to obtain a second radio frequency signal, and transmit the second radio frequency signal to a target user.

[0040] Specifically, the second radio frequency signal refers to a radio frequency signal that contains target communication data after being modulated.

[0041] After the target communication data is generated, it needs to be modulated by the RF processing unit to meet the transmission requirements of the wireless channel. The modulation process involves converting the digital signal into a radio frequency signal suitable for wireless transmission. This process needs to comply with specific wireless communication standards and protocols. After the modulation is completed, the resulting second radio frequency signal contains the original target communication data. The RF processing unit then transmits this second radio frequency signal through the wireless channel. During the transmission process, it is necessary to ensure that parameters such as signal strength, frequency, and phase meet wireless communication standards to ensure that the signal can be accurately received by the target user.

[0042] Furthermore, when the power management unit indicates that the power is in a healthy state, step S10 includes the following steps:

[0043] S11: Setting the power supply temperature constraint range, power supply power threshold, and power supply voltage constraint range;

[0044] S12: When the power monitoring temperature falls within the power temperature constraint range, the remaining power of the power supply is greater than the power supply power threshold, and the power monitoring voltage falls within the power voltage constraint range, displaying that the power management unit is in a power health state;

[0045] S13: Otherwise, displaying the power management unit as being in an unhealthy power state.

[0046] Specifically, the power management unit refers to the component in the smart wearable chip that is responsible for monitoring and managing the power status. It ensures that the chip operates with sufficient and stable power; the power temperature constraint range is a temperature range set to ensure power safety and performance, and the power operating temperature must be within this range; the power power threshold is the set minimum power level to ensure that the chip has sufficient power to maintain normal operation; the power voltage constraint range is a voltage range set to ensure power stability, and the power voltage must be within this range.

[0047] When the temperature detected by the power monitoring system is within the set power temperature constraint range, the remaining power is greater than the set power threshold, and the monitored voltage is within the set power voltage constraint range, the power management unit will display that the chip is in a healthy power state, which means that the chip can safely perform communication and data processing tasks.

[0048] If any parameter exceeds the set range, the power management unit will indicate that the chip is in an unhealthy power state. At this time, the chip may need to take measures such as reducing power consumption, prompting the user to charge, or automatically shutting down to protect the chip from damage.

[0049] This ensures the chip operates in a healthy power state, preventing chip failure or performance degradation caused by power problems, thereby improving chip reliability and user trust. For example, when a wearable device is used outdoors for an extended period of time, the ambient temperature may fluctuate. By monitoring the power supply temperature and ensuring it remains within a safe range, the chip can avoid performance degradation or damage caused by overheating, ensuring stable chip operation in a variety of environments.

[0050] Furthermore, the power supply temperature constraint interval, the power supply power threshold, and the power supply voltage constraint interval are set. Step S11 includes the following steps:

[0051] S111: Obtain power monitoring information, wherein the power monitoring information includes power timing information, power temperature information at the time zone starting point, and ambient temperature information;

[0052] S112: Inputting the power supply power timing information, the power supply temperature information at the time zone starting point, and the ambient temperature information into a power supply temperature prediction model for analysis to obtain the power supply temperature constraint interval;

[0053] S113: Inputting the power supply power timing information into a voltage calibration table for identification to obtain the power supply voltage constraint range;

[0054] S114: Setting the power level threshold via the management backend.

[0055] Specifically, power monitoring information refers to the data collected from the power management unit of the smart wearable chip, including power supply timing information and ambient temperature information; power supply timing information records the changes in power supply power over time, while ambient temperature information provides temperature data of the power supply working environment; the power supply temperature prediction model is an algorithm or mathematical model used to predict the operating temperature of the power supply based on the input power supply timing information, time zone starting point power supply temperature information and ambient temperature information, and determine the power supply temperature constraint range accordingly; the power supply voltage constraint range is the voltage safety range determined based on the power supply timing information and voltage calibration table; the management background refers to the software interface or system used to configure and monitor the operating parameters of the smart wearable chip, which allows users or system administrators to set power supply thresholds.

[0056] Furthermore, the voltage calibration table is a pre-set data table that stores one-to-one correspondence between power supply power and voltage constraint intervals. The voltage constraint interval can be indexed in the voltage calibration table according to the end-time power of the power supply power timing information.

[0057] The power supply temperature prediction model is an intelligent model built based on machine learning. The detailed configuration process is as follows:

[0058] Furthermore, the power supply temperature prediction model construction step includes:

[0059] According to the smart wearable chip model, collect the power supply power recording timing information of the preset time zone, the power supply recording temperature information of the time zone starting point, the environmental recording temperature information and the power supply temperature identification interval. The preset time zone represents the time zone of the preset time step forward from the current moment;

[0060] Construct a power supply temperature prediction loss function:

[0061]

[0062] Wherein, LOSS1 represents the power supply temperature prediction loss, f{[x1, x2]∩[y1, y2]} represents the interval length of the intersection interval of the interval [x1, x2] and the interval [y1, y2], g{[x1, x2]∪[y1, y2]} represents the interval length of the union interval of the interval [x1, x2] and the interval [y1, y2], [x1, x2] represents the predicted power supply temperature interval, and [y1, y2] represents the power supply temperature identification interval;

[0063] According to the power supply temperature prediction loss function, the power supply power record timing information, the power supply record temperature information at the starting point of the time zone, the environment record temperature information and the power supply temperature identification interval are retrieved, and a long short-term memory neural network is trained to obtain the power supply temperature prediction model.

[0064] Specifically, the smart wearable chip model is the chip model. With the smart wearable chip model as a constraint, the time zone of the preset time step forward from the current moment is collected, that is, the power power recording timing information of the preset time zone, the power recording temperature information of the starting point of the time zone, the environmental recording temperature information and the power temperature identification interval.

[0065] Preferably, the sampling process is as follows: each set of historical data of the chip's normal operation sample data includes a set of one-to-one corresponding power supply power recording timing information, time zone starting point power supply recording temperature information, environment recording temperature information and power supply temperature recording data.

[0066] Configure the power deviation threshold, power supply temperature deviation threshold, and ambient temperature deviation threshold. When the power mean deviation of the power supply power record time series information is less than the power deviation threshold, the power supply temperature deviation of the power supply temperature information at the time zone start point is less than the power supply temperature deviation threshold, and the ambient temperature deviation of the ambient temperature information is less than the ambient temperature deviation threshold, the power supply temperature record data of the two groups are merged and divided into the same cluster.

[0067] Sampling is continued until the data volume of the power supply temperature record data of the same cluster meets the pre-set data volume threshold, and any one group of multiple groups of power supply power record timing information, time zone starting point power supply record temperature information, and environmental record temperature information corresponding to the power supply temperature record data of the same cluster is extracted, and the power supply power record timing information, time zone starting point power supply record temperature information, and environmental record temperature information are selected as training data; at the same time, the outliers of the power supply temperature record data of the same cluster are deleted, and the power supply temperature interval of the concentrated point distribution is recorded as the power supply temperature identification interval.

[0068] Furthermore, a power supply temperature prediction loss function is constructed: The power supply power record timing information, the power supply record temperature information at the starting point of the time zone, and the environment record temperature information are taken as input data, and the power supply temperature identification interval is used as output data to train a long short-term memory neural network. When at least 950 groups of output losses are less than the loss threshold after 1000 consecutive training times, the power supply temperature prediction model is obtained.

[0069] Further, when the target communication data attribute does not exist in the storage unit, the target communication data attribute is sent to the application processor unit for computing power requirement analysis to obtain the expected computing power. Step S20 includes the following steps:

[0070] S21: matching and generating historical data according to the target communication data attributes, wherein the generated historical data includes a plurality of computing power consumption record values;

[0071] S22: performing a centralized trend analysis on the plurality of computing power consumption record values ​​to obtain a centralized computing power consumption record value;

[0072] S23: Calculate the average of the recorded values ​​of the consumed computing power and set it as the expected computing power.

[0073] Specifically, generated historical data refers to data records of past processing tasks related to the target communication data attributes, including several recorded values ​​of computing power consumption; the recorded value of computing power consumption is the quantitative value of the computing resources actually consumed during the processing of historical tasks; central trend analysis is a statistical method used to determine the central position or general level of data, which may include calculating statistical quantities such as the mean, median or mode; the concentrated recorded value of computing power consumption refers to the typical value of computing power consumption obtained after central trend analysis; the expected computing power is set based on the mean of the concentrated recorded values ​​of computing power consumption, which represents the ideal or expected computing power required to process the target communication data attributes.

[0074] Matching the expected computing power requirements can ensure the reasonable allocation of computing resources according to the actual needs of the task, improving processing efficiency and energy utilization

[0075] Furthermore, when the expected computing power is greater than or equal to the edge activation computing power threshold, configuring the edge computing power node includes:

[0076] When the expected computing power is greater than or equal to the edge activation computing power threshold, obtaining a list of edge computing power nodes with computing power redundancy and a list of computing power redundancy amounts;

[0077] The number of scheduling nodes and node scheduling distance are used as fitness evaluation indicators to construct the fitness function:

[0078] f(n, d) = log a n+log b d,

[0079] Where f(n, d) represents the scheduling fitness function, n represents the number of scheduling nodes, d represents the scheduling distance, a and b represent the weight adjustment index, and both a and b are greater than 1;

[0080] Randomly configuring a scheduling scheme based on the computing power redundancy list and the edge computing power node list to obtain multiple edge computing power node scheduling schemes, wherein the sum of the computing power of any edge computing power node scheduling scheme is greater than or equal to the expected computing power;

[0081] According to the fitness function, the plurality of edge computing node scheduling schemes are sorted with the minimum fitness, a selected edge computing node scheduling scheme is obtained, and the edge computing node is configured.

[0082] Specifically, the edge activation computing power threshold is a preset computing power value. When the expected computing power reaches or exceeds this threshold, the edge computing power node needs to be activated to provide additional computing resources; the edge computing power node list is a list of all available edge computing nodes that have the ability to provide the required computing power; the computing power redundancy list details the amount by which the available computing power of each edge computing power node exceeds its current task requirements; the fitness evaluation index is a standard used to evaluate the quality of the edge computing power node scheduling scheme, including the number of scheduling nodes and the node scheduling distance; the fitness function f(n, d) = log a n+log b d is used to calculate the fitness score of the scheduling plan based on the fitness evaluation index; the weight adjustment indexes a and b are parameters in the fitness function, which are used to adjust the importance of different evaluation indicators. They are both greater than 1.

[0083] Based on the list of redundant computing power and the list of edge computing nodes, the system randomly configures scheduling plans, generating multiple edge computing node scheduling plans to ensure that the sum of the computing power of each plan meets the expected computing power requirements. Finally, the system evaluates these scheduling plans based on the fitness function, selects the plan with the lowest fitness score as the final edge computing node scheduling plan, and configures the edge computing nodes accordingly.

[0084] The above steps ensure that when the expected computing power is high, the smart wearable chip can effectively utilize edge computing resources to optimize task processing efficiency and response speed. For example, if a complex data analysis task requires computing power beyond the chip's local processing capabilities, the system can use the above steps to quickly find the optimal combination of edge computing nodes to support the task, thereby improving overall computing efficiency and user experience.

[0085] Furthermore, communicating with the edge computing node and generating the target communication data attributes in combination with the storage unit to obtain the target communication data includes:

[0086] Obtaining a generated mapping set of the target communication data attributes;

[0087] According to the generated mapping set, matching the underlying mapping data;

[0088] The mapping underlying data is extracted from the storage unit and sent to the edge computing node to generate the target communication data attributes to obtain the target communication data.

[0089] Specifically, edge computing nodes refer to devices or services that provide additional computing power at the edge of the network to assist smart wearable chips in processing tasks that require a lot of computing power; the generation mapping set of target communication data attributes refers to the set of data generation rules or patterns associated with the target communication data attributes, and users can pre-set various mapping functions and rules; mapping underlying data refers to the basic data actually stored in the storage unit of the smart wearable chip and associated with the target communication data attributes.

[0090] Specifically, after the smart wearable chip establishes a communication connection with the edge computing node, the chip generates the target communication data based on the data in the storage unit. First, the system obtains a set of generated mappings for the target communication data attributes. These mappings define how to generate the required target communication data from the underlying data. Next, based on these generated mappings, the system matches the corresponding mapped underlying data in the storage unit, which is required to generate the target communication data. Finally, the system extracts these mapped underlying data from the storage unit and sends them to the edge computing node, so that the node's computing power can be used to process and generate the target communication data attributes, ultimately obtaining the target communication data.

[0091] The communication control method based on the smart wearable chip provided by the embodiment of the present invention has at least the following technical effects:

[0092] When the power management unit indicates that the power is in a healthy state, the RF processing unit receives the first radio frequency signal and analyzes it to obtain a user communication instruction, wherein the user communication instruction has the target communication data attribute and is sent to the application processor unit for computing power demand analysis to obtain the expected computing power; when it is greater than or equal to the edge activation computing power threshold, the edge computing power node is configured and combined with the storage unit to obtain the target communication data; the RF processing unit performs modulation to obtain a second radio frequency signal and transmit it to the target user. The use of edge computing power nodes to map target communication data that the storage unit does not have realizes high-level semantic mapping interaction, achieving the technical effect of improving the intelligence level of wearable chips.

[0093] Example 2:

[0094] like Figure 2 As shown, based on the same inventive concept as the communication control method based on the smart wearable chip provided in Example 1, the embodiment of the present invention also provides a communication control system based on the smart wearable chip, which is applied to the communication control system based on the smart wearable chip. The system is deployed on the smart wearable chip, and the smart wearable chip includes a power management unit, an application processor unit, a storage unit and a wireless communication unit. The wireless communication unit includes an RF processing unit, including:

[0095] a communication instruction parsing module, configured to, when the power management unit indicates that the power is in a healthy state, receive the first radio frequency signal through the RF processing unit for parsing to obtain a user communication instruction, wherein the user communication instruction has a target communication data attribute;

[0096] a demand computing power parsing module, configured to, when the target communication data attribute does not exist in the storage unit, send the target communication data attribute to the application processor unit for computing power demand parsing to obtain the expected computing power;

[0097] An edge node configuration module, configured to configure an edge computing power node when the expected computing power is greater than or equal to the edge activation computing power threshold;

[0098] A communication data generation module is used to communicate with the edge computing node and generate the target communication data attributes in combination with the storage unit to obtain the target communication data;

[0099] The communication task execution module is configured to modulate the target communication data through the RF processing unit to obtain a second radio frequency signal, and transmit the second radio frequency signal to a target user.

[0100] Furthermore, when the power management unit indicates that the power is in a healthy state, it includes:

[0101] Set the power supply temperature constraint range, power supply power threshold and power supply voltage constraint range;

[0102] When the power monitoring temperature falls within the power temperature constraint range, the remaining power of the power supply is greater than the power supply power threshold, and the power monitoring voltage falls within the power voltage constraint range, the power management unit is displayed as being in a power health state;

[0103] Otherwise, the power management unit is displayed as being in an unhealthy power state.

[0104] Furthermore, setting the power supply temperature constraint range, power supply power threshold, and power supply voltage constraint range includes:

[0105] Obtaining power monitoring information, wherein the power monitoring information includes power timing information, time zone starting power temperature information, and ambient temperature information;

[0106] Inputting the power supply power timing information, the power supply temperature information at the time zone starting point, and the ambient temperature information into a power supply temperature prediction model for analysis to obtain the power supply temperature constraint interval;

[0107] Inputting the power supply power timing information into a voltage calibration table for identification to obtain the power supply voltage constraint range;

[0108] The power level threshold is set through the management backend.

[0109] Furthermore, the power supply temperature prediction model construction step includes:

[0110] According to the smart wearable chip model, collect the power supply power recording timing information of the preset time zone, the power supply recording temperature information of the time zone starting point, the environmental recording temperature information and the power supply temperature identification interval. The preset time zone represents the time zone of the preset time step forward from the current moment;

[0111] Construct a power supply temperature prediction loss function:

[0112]

[0113] Wherein, LOSS1 represents the power supply temperature prediction loss, f{[x1, x2]∩[y1, y2]} represents the interval length of the intersection interval of the interval [x1, x2] and the interval [y1, y2], g{[x1, x2]∪[y1, y2]} represents the interval length of the union interval of the interval [x1, x2] and the interval [y1, y2], [x1, x2] represents the predicted power supply temperature interval, and [y1, y2] represents the power supply temperature identification interval;

[0114] According to the power supply temperature prediction loss function, the power supply power record timing information, the power supply record temperature information at the starting point of the time zone, the environment record temperature information and the power supply temperature identification interval are retrieved, and a long short-term memory neural network is trained to obtain the power supply temperature prediction model.

[0115] Further, when the target communication data attribute does not exist in the storage unit, the target communication data attribute is sent to the application processor unit for computing power requirement analysis to obtain the expected computing power, including:

[0116] Matching and generating historical data according to the target communication data attributes, wherein the generated historical data includes a plurality of consumed computing power record values;

[0117] Performing a centralized trend analysis on the plurality of computing power consumption record values ​​to obtain a centralized computing power consumption record value;

[0118] The average of the recorded values ​​of the consumed computing power is calculated and set as the expected computing power.

[0119] Furthermore, when the expected computing power is greater than or equal to the edge activation computing power threshold, configuring the edge computing power node includes:

[0120] When the expected computing power is greater than or equal to the edge activation computing power threshold, obtaining a list of edge computing power nodes with computing power redundancy and a list of computing power redundancy amounts;

[0121] The number of scheduling nodes and node scheduling distance are used as fitness evaluation indicators to construct the fitness function:

[0122] f(n, d) = log a n+log b d,

[0123] Where f(n, d) represents the scheduling fitness function, n represents the number of scheduling nodes, d represents the scheduling distance, a and b represent the weight adjustment index, and both a and b are greater than 1;

[0124] Randomly configuring a scheduling scheme based on the computing power redundancy list and the edge computing power node list to obtain multiple edge computing power node scheduling schemes, wherein the sum of the computing power of any edge computing power node scheduling scheme is greater than or equal to the expected computing power;

[0125] According to the fitness function, the plurality of edge computing node scheduling schemes are sorted with the minimum fitness, a selected edge computing node scheduling scheme is obtained, and the edge computing node is configured.

[0126] Furthermore, communicating with the edge computing node and generating the target communication data attributes in combination with the storage unit to obtain the target communication data includes:

[0127] Obtaining a generated mapping set of the target communication data attributes;

[0128] According to the generated mapping set, matching the underlying mapping data;

[0129] The mapping underlying data is extracted from the storage unit and sent to the edge computing node to generate the target communication data attributes to obtain the target communication data.

[0130] Example 3:

[0131] See also Figure 3 , Figure 3 Schematic diagram of an embodiment of an electronic device provided by an embodiment of the present invention. Figure 3 As shown, an embodiment of the present invention provides an electronic device 500, including a memory 510, a processor 520, and a first computer program 511 stored in the memory 510 and executable on the processor 520. When the processor 520 executes the first computer program 511, the following steps are implemented:

[0132] When the power management unit indicates that the power is in a healthy state, the RF processing unit receives and analyzes the first radio frequency signal to obtain a user communication instruction, wherein the user communication instruction has a target communication data attribute;

[0133] When the target communication data attribute does not exist in the storage unit, the target communication data attribute is sent to the application processor unit for computing power requirement analysis to obtain the expected computing power;

[0134] When the expected computing power is greater than or equal to the edge activation computing power threshold, configuring the edge computing power node;

[0135] Communicate with the edge computing node, generate the target communication data attributes in conjunction with the storage unit, and obtain the target communication data;

[0136] The target communication data is modulated by the RF processing unit to obtain a second radio frequency signal, and the second radio frequency signal is transmitted to a target user.

[0137] Example 4:

[0138] See also Figure 4 , Figure 4 Schematic diagram of an embodiment of a computer-readable storage medium provided in an embodiment of the present invention. Figure 4 As shown, this embodiment provides a computer-readable storage medium 600, on which a second computer program 611 is stored. When the second computer program 611 is executed by a processor, the following steps are implemented:

[0139] When the power management unit indicates that the power is in a healthy state, the RF processing unit receives and analyzes the first radio frequency signal to obtain a user communication instruction, wherein the user communication instruction has a target communication data attribute;

[0140] When the target communication data attribute does not exist in the storage unit, the target communication data attribute is sent to the application processor unit for computing power requirement analysis to obtain the expected computing power;

[0141] When the expected computing power is greater than or equal to the edge activation computing power threshold, configuring the edge computing power node;

[0142] Communicate with the edge computing node, generate the target communication data attributes in conjunction with the storage unit, and obtain the target communication data;

[0143] The target communication data is modulated by the RF processing unit to obtain a second radio frequency signal, and the second radio frequency signal is transmitted to a target user.

[0144] It should be noted that, in the above embodiments, the description of each embodiment has its own focus. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant description of other embodiments.

[0145] It will be understood by those skilled in the art that embodiments of the present invention may be provided as methods, systems, or computer program products. Thus, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware. Furthermore, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0146] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowcharts and / or block diagrams, as well as combinations of processes and / or blocks in the flowcharts and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded computer, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowcharts and / or block diagrams. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0147] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0148] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0149] Although preferred embodiments of the present invention have been described, additional changes and modifications to these embodiments may occur to those skilled in the art once the basic inventive concepts become known.

[0150] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the present invention and its equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. A communication control method based on a smart wearable chip, characterized in that: Applied to a communication control system based on a smart wearable chip. The system is deployed on the smart wearable chip. The smart wearable chip includes a power management unit, an application processor unit, a storage unit, and a wireless communication unit. The wireless communication unit includes an RF processing unit, including: When the power management unit indicates that the power is in a healthy state, the RF processing unit receives and analyzes the first radio frequency signal to obtain a user communication instruction, wherein the user communication instruction has a target communication data attribute; When the target communication data attribute does not exist in the storage unit, the target communication data attribute is sent to the application processor unit for computing power requirement analysis to obtain the expected computing power; When the expected computing power is greater than or equal to the edge activation computing power threshold, configuring the edge computing power node; Communicate with the edge computing node, generate the target communication data attributes in conjunction with the storage unit, and obtain the target communication data; The target communication data is modulated by the RF processing unit to obtain a second radio frequency signal, and the second radio frequency signal is transmitted to a target user.

2. The method according to claim 1, wherein When the power management unit displays the power health status, it includes: Set the power supply temperature constraint range, power supply power threshold and power supply voltage constraint range; When the power monitoring temperature falls within the power temperature constraint range, the remaining power of the power supply is greater than the power supply power threshold, and the power monitoring voltage falls within the power voltage constraint range, the power management unit is displayed as being in a power health state; Otherwise, the power management unit is displayed as being in an unhealthy power state.

3. The method according to claim 2, wherein Set the power supply temperature constraint range, power supply power threshold, and power supply voltage constraint range, including: Obtaining power monitoring information, wherein the power monitoring information includes power timing information, time zone starting power temperature information, and ambient temperature information; Inputting the power supply power timing information, the power supply temperature information at the time zone starting point, and the ambient temperature information into a power supply temperature prediction model for analysis to obtain the power supply temperature constraint interval; Inputting the power supply power timing information into a voltage calibration table for identification to obtain the power supply voltage constraint range; The power level threshold is set through the management backend.

4. The method according to claim 3, wherein The power supply temperature prediction model construction step includes: According to the smart wearable chip model, collect the power supply power recording timing information of the preset time zone, the power supply recording temperature information of the time zone starting point, the environmental recording temperature information and the power supply temperature identification interval. The preset time zone represents the time zone of the preset time step forward from the current moment; Construct a power supply temperature prediction loss function: Among them, it represents the power supply temperature prediction loss, represents the interval length of the intersection interval of intervals, represents the interval length of the union interval of intervals, represents the predicted power supply temperature interval, and represents the power supply temperature identification interval; According to the power supply temperature prediction loss function, the power supply power record timing information, the power supply record temperature information at the starting point of the time zone, the environment record temperature information and the power supply temperature identification interval are retrieved, and a long short-term memory neural network is trained to obtain the power supply temperature prediction model.

5. The method according to claim 1, wherein When the target communication data attribute does not exist in the storage unit, the target communication data attribute is sent to the application processor unit for computing power requirement analysis to obtain the expected computing power, including: Matching and generating historical data according to the target communication data attributes, wherein the generated historical data includes a plurality of consumed computing power record values; Performing a centralized trend analysis on the plurality of computing power consumption record values ​​to obtain a centralized computing power consumption record value; The average of the recorded values ​​of the consumed computing power is calculated and set as the expected computing power.

6. The method according to claim 1, wherein When the expected computing power is greater than or equal to the edge activation computing power threshold, configuring the edge computing power node includes: When the expected computing power is greater than or equal to the edge activation computing power threshold, obtaining a list of edge computing power nodes with computing power redundancy and a list of computing power redundancy amounts; The number of scheduling nodes and node scheduling distance are used as fitness evaluation indicators to construct the fitness function: f(n,d)=log a n+log b d, Where f(n,d) represents the scheduling fitness function, n represents the number of scheduling nodes, d represents the scheduling distance, a and b represent the weight adjustment index, and both a and b are greater than 1; Randomly configuring a scheduling scheme based on the computing power redundancy list and the edge computing power node list to obtain multiple edge computing power node scheduling schemes, wherein the sum of the computing power of any edge computing power node scheduling scheme is greater than or equal to the expected computing power; According to the fitness function, the plurality of edge computing node scheduling schemes are sorted with the minimum fitness, a selected edge computing node scheduling scheme is obtained, and the edge computing node is configured.

7. The method according to claim 1, wherein Communicating with the edge computing node, generating the target communication data attributes in conjunction with the storage unit to obtain the target communication data, including: Obtaining a generated mapping set of the target communication data attributes; According to the generated mapping set, matching the underlying mapping data; The mapping underlying data is extracted from the storage unit and sent to the edge computing node to generate the target communication data attributes to obtain the target communication data.

8. The communication control system based on the smart wearable chip is characterized by: Applied to a communication control system based on a smart wearable chip. The system is deployed on the smart wearable chip. The smart wearable chip includes a power management unit, an application processor unit, a storage unit, and a wireless communication unit. The wireless communication unit includes an RF processing unit, including: a communication instruction parsing module, configured to, when the power management unit indicates that the power is in a healthy state, receive the first radio frequency signal through the RF processing unit for parsing to obtain a user communication instruction, wherein the user communication instruction has a target communication data attribute; a demand computing power parsing module, configured to, when the target communication data attribute does not exist in the storage unit, send the target communication data attribute to the application processor unit for computing power demand parsing to obtain the expected computing power; An edge node configuration module, configured to configure an edge computing power node when the expected computing power is greater than or equal to the edge activation computing power threshold; A communication data generation module is used to communicate with the edge computing node and generate the target communication data attributes in combination with the storage unit to obtain the target communication data; The communication task execution module is configured to modulate the target communication data through the RF processing unit to obtain a second radio frequency signal, and transmit the second radio frequency signal to a target user.

9. An electronic device, characterized in that: include: Memory for storing computer software programs; A processor is used to read and execute the computer software program, thereby implementing the communication control method based on the smart wearable chip as described in any one of claims 1 to 7.

10. A non-transitory computer-readable storage medium, characterized in that The storage medium stores a computer software program, which, when executed by a processor, implements the communication control method based on a smart wearable chip according to any one of claims 1 to 7.

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