Communication method and system for embedded device based on internet of things communication

Abstract

The application discloses a communication method and system of embedded equipment based on Internet of Things communication, and relates to the technical field of communication methods. The final communication mode of the embedded equipment is determined based on the node form of multiple communication nodes of the communication path and the network state of the embedded equipment. The online communication event of the embedded equipment is determined based on the final communication mode, the interactive signal of the embedded equipment and the corresponding multiple communication parameters, thereby realizing the accuracy of the online communication event of the embedded equipment. Therefore, the multi-dimensional communication system of the embedded equipment is determined according to multiple sub-communication maintenance measures of the communication maintenance event, the online communication process of the embedded equipment and the communication progress of the to-be-received data of the embedded equipment. The dynamic communication event of the embedded equipment is determined according to the multi-dimensional communication system of the embedded equipment, the data load state of the embedded equipment and the service life of the embedded equipment, thereby improving the accuracy of the dynamic communication event of the embedded equipment.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of communication methods, and particularly relates to a communication method and system of embedded equipment based on Internet of Things communication. BACKGROUND

[0002] With the development of science and technology, embedded equipment is gradually applied to people's life, and lithium battery energy management equipment as one of the embedded equipment manages the energy of lithium batteries. In the prior art, interactive data of the embedded equipment is collected, online communication events of the embedded equipment are determined according to the interactive data of the embedded equipment and corresponding interactive equipment, and the communication mode and multiple communication parameters of the embedded equipment are ignored, which affects the accuracy of the online communication events of the embedded equipment, and a multi-dimensional communication system in China cannot be constructed, so that dynamic communication events of the embedded equipment cannot be output. SUMMARY

[0003] The present application provides a communication method and system of embedded equipment based on Internet of Things communication.

[0004] The present application provides a communication method of embedded equipment based on Internet of Things communication, which comprises the following steps.

[0005] According to the multiple interactive data of the data interaction space of the embedded equipment and the current position of the embedded equipment, the Internet of Things communication mode of the embedded equipment is determined.

[0006] According to the identification of the Internet of Things communication mode, multiple sub-Internet of Things communication projects are determined, and according to the project content of each sub-Internet of Things communication project and the to-be-received data of the embedded equipment, the communication path of the embedded equipment is determined.

[0007] According to the node form of the multiple communication nodes of the communication path and the network state of the embedded equipment, the final communication mode of the embedded equipment is determined, and according to the final communication mode, the interactive signal of the embedded equipment and the corresponding multiple communication parameters, the online communication event of the embedded equipment is determined.

[0008] According to the detection of the online communication process, multiple abnormal communication nodes are determined, and according to the node position of each abnormal communication node, the corresponding communication range in the communication path and the online communication event, the communication maintenance event is determined.

[0009] According to the multiple sub-communication maintenance measures of the communication maintenance event, the online communication process of the embedded device and the communication progress of the to-be-received data of the embedded device, the multi-dimensional communication system of the embedded device is determined, and according to the multi-dimensional communication system of the embedded device, the data load state of the embedded device and the service life of the embedded device, the dynamic communication event of the embedded device is determined.

[0010] The embodiment of the application provides a communication system of an embedded device based on Internet of Things communication, which is applied to the communication method of the embedded device based on Internet of Things communication.

[0011] The Internet of Things communication mode module is used for determining a corresponding data interaction space based on a database of the embedded device, determining an Internet of Things communication mode of the embedded device according to multiple interaction data of the data interaction space of the embedded device and a current position of the embedded device;

[0012] The communication path module is used for determining multiple sub-Internet of Things communication items according to the identification of the Internet of Things communication mode, and determining a communication path of the embedded device based on item content of each sub-Internet of Things communication item and to-be-received data of the embedded device;

[0013] The online communication event module is used for determining a final communication mode of the embedded device based on a node form of multiple communication nodes of the communication path and a network state of the embedded device, and determining an online communication event of the embedded device based on the final communication mode, an interaction signal of the embedded device and multiple corresponding communication parameters;

[0014] The communication maintenance event module is used for determining multiple abnormal communication nodes based on detection of the online communication process, and determining a communication maintenance event according to a node position of each abnormal communication node, a corresponding communication range in the communication path and the online communication event;

[0015] The dynamic communication event module is used for determining a multi-dimensional communication system of the embedded device according to multiple sub-communication maintenance measures of the communication maintenance event, the online communication process of the embedded device and the communication progress of the to-be-received data of the embedded device, and determining a dynamic communication event of the embedded device according to the multi-dimensional communication system of the embedded device, a data load state of the embedded device and a service life of the embedded device.

[0016] Compared with the prior art, the application has the following beneficial effects:

[0017] In the embodiment of the present application, through the method in the embodiment of the present application, the corresponding data interaction space is determined based on the database of the embedded device, the Internet of Things communication mode of the embedded device is determined according to the plurality of interaction data of the data interaction space of the embedded device and the current position of the embedded device, a plurality of sub Internet of Things communication items are determined according to the identification of the Internet of Things communication mode, the communication path of the embedded device is determined based on the project content of each sub Internet of Things communication item and the to-be-received data of the embedded device, the final communication mode of the embedded device is determined based on the node form of the plurality of communication nodes of the communication path and the network state of the embedded device, and the online communication event of the embedded device is determined based on the final communication mode, the interaction signal of the embedded device and the corresponding plurality of communication parameters. The communication path of the embedded device is introduced, the overall consideration of the final communication mode, the interaction signal of the embedded device and the corresponding plurality of communication parameters is compatible, and the accuracy of the online communication event of the embedded device is realized.

[0018] Therefore, based on the detection of the online communication process, a plurality of abnormal communication nodes are determined, a communication maintenance event is determined according to the node position of each abnormal communication node, the corresponding communication range in the communication path and the online communication event, a multi-dimensional communication system of the embedded device is determined according to a plurality of sub communication maintenance measures of the communication maintenance event, the online communication process of the embedded device and the communication progress of the to-be-received data of the embedded device, a dynamic communication event of the embedded device is determined according to the multi-dimensional communication system of the embedded device, the data load state of the embedded device and the service life of the embedded device, the communication maintenance event is introduced, the multi-dimensional communication system is further controlled, the overall consideration of the multi-dimensional communication system of the embedded device, the data load state of the embedded device and the service life of the embedded device is realized, and the accuracy of the dynamic communication event of the embedded device is improved. BRIEF DESCRIPTION OF DRAWINGS

[0019] Figure 1 is a flowchart of the communication method of the embedded device based on Internet of Things communication in the embodiment of the present application;

[0020] Figure 2 is a flowchart of step S11 in the communication method of the embedded device based on Internet of Things communication in the embodiment of the present application;

[0021] Figure 3 is a flowchart of step S12 in the communication method of the embedded device based on Internet of Things communication in the embodiment of the present application;

[0022] Figure 4 is a flowchart of step S13 in the communication method of the embedded device based on Internet of Things communication in the embodiment of the present application;

[0023] Figure 5is the flowchart of step S14 in the communication method of the embedded device based on Internet of Things communication in the embodiment of the application;

[0024] Figure 6 is the flowchart of step S15 in the communication method of the embedded device based on Internet of Things communication in the embodiment of the application;

[0025] Figure 7 is the structural composition diagram of the communication system of the embedded device based on Internet of Things communication in the embodiment of the application. DETAILED DESCRIPTION

[0026] The technical solutions in the embodiments of the application will be clearly and completely described below with reference to the drawings in the embodiments of the application.

[0027] Please refer to Figures 1 to 7 A communication method of an embedded device based on Internet of Things communication, applied to a communication scene; the communication method of the embedded device based on Internet of Things communication comprises the following steps.

[0028] Step S11: determining a corresponding data interaction space based on a database of the embedded device, determining an Internet of Things communication mode of the embedded device according to a plurality of interaction data of the data interaction space of the embedded device and a current position of the embedded device;

[0029] Step S12: determining a plurality of sub Internet of Things communication items according to the identification of the Internet of Things communication mode, determining a communication path of the embedded device based on item content of each sub Internet of Things communication item and to-be-received data of the embedded device;

[0030] Step S13: determining a final communication mode of the embedded device based on node forms of a plurality of communication nodes of the communication path and a network state of the embedded device, determining an online communication event of the embedded device based on the final communication mode, an interaction signal of the embedded device and a plurality of corresponding communication parameters;

[0031] Step S14: determining a plurality of abnormal communication nodes based on detection of the online communication process, determining a communication maintenance event according to a node position of each abnormal communication node, a corresponding communication range in the communication path and the online communication event;

[0032] Step S15: determining a multi-dimensional communication system of the embedded device according to a plurality of sub communication maintenance measures of the communication maintenance event, an online communication process of the embedded device and a communication progress of the to-be-received data of the embedded device, determining a dynamic communication event of the embedded device according to the multi-dimensional communication system of the embedded device, a data load state of the embedded device and a service life of the embedded device.

[0033] Reference Figure 2In step S11, the specific steps are:

[0034] S111: Collecting the database of the embedded device, determining a plurality of data spaces according to traversal of the database of the embedded device, determining a corresponding data interaction space based on identification of the plurality of data spaces, monitoring the data interaction space in real time, and determining a plurality of interaction data according to matching of the data interaction space and the embedded device;

[0035] S112: Collecting the current position of the embedded device, determining a plurality of environmental parameters and scene features according to detection of the current position of the embedded device, determining the current communication scene of the embedded device according to the plurality of environmental parameters and scene features, and determining the Internet of Things communication mode of the embedded device based on the current communication scene of the embedded device, the plurality of interaction data, and the working state of the to-be-interacted device.

[0036] In the embodiment of the present application, the database of the embedded device is collected, a plurality of data spaces are determined according to traversal of the database of the embedded device, a corresponding data interaction space is determined based on identification of the plurality of data spaces, the data interaction space is monitored in real time, and a plurality of interaction data are determined according to matching of the data interaction space and the embedded device, which is compatible with the overall consideration of matching of the data interaction space and the embedded device, and ensures the accuracy of the plurality of interaction data.

[0037] At this time, in the embedded system, the "database" usually refers to a structured data area stored in a non-volatile memory (such as Flash), which can be in the form of a configuration file, a data structure array, or a device description table; when the system is initialized, it will read the metadata of these data, such as the number of modules, the offset, etc., through a traversal algorithm; the purpose of traversal is to construct a complete "data space registry" in memory, which is like an index list of all data items of the device, clearly listing the ID, type, access permission, and other core attributes of each data module.

[0038] After having a complete data space registry, the system needs to filter out the part that really needs to communicate with the outside world, which is achieved by checking the attribute flag bit of each data module, such as isReportable (whether to actively report) and isObservable (whether to be queried); only when at least one of these flag bits is true, the corresponding data module will be marked as a "data interaction space", this process effectively filters out those data that are only used within the device and do not need to be exposed to the outside, thereby simplifying the subsequent monitoring and processing range, and finally generating an "interaction space activation list".

[0039] After identifying the data that needs to be interacted, the system will start a continuous monitoring mechanism to track their state changes, which usually runs in the form of background tasks or interrupt service programs, and can be in the form of polling or event-driven. Polling is to check the value of all data items at a fixed time, while event-driven is triggered by hardware interrupts when sensor data is updated or state changes, which is more efficient. The core of monitoring is to maintain a state flag (such as DATA_DIRTY) for each data module in the interaction space. Once the data changes, it will be immediately marked, preparing for subsequent data matching.

[0040] When the monitoring mechanism finds that a certain data module is marked as "dirty data", it will trigger the matching logic. This logic will determine whether it needs to generate interaction data immediately according to the preset reporting strategy (such as change threshold, time interval or emergency threshold). If the matching is successful, the system will extract the current value from the data space and encapsulate it according to the predefined format (such as JSON, CBOR) to form an "interaction data unit" containing data values, timestamps, module IDs and other meta-information. These ready-to-use data units are placed in the sending queue, waiting for the next communication processing.

[0041] Further, the current position of the embedded device is collected, and a plurality of environmental parameters and scene features are determined according to the detection of the current position of the embedded device. The current communication scene of the embedded device is determined according to the plurality of environmental parameters and scene features. The Internet of Things communication mode of the embedded device is determined based on the current communication scene of the embedded device, the plurality of interaction data, and the working state of the to-be-interacted device. The current communication scene of the embedded device, the plurality of interaction data, and the working state of the to-be-interacted device are compatible, and the accuracy of the Internet of Things communication mode of the embedded device is ensured.

[0042] At this time, the device perceives its own position by fusing multiple positioning technologies, such as using GNSS to obtain accurate coordinates outdoors, and scanning Wi-Fi access points or Bluetooth beacons to infer regional positions indoors. After obtaining the original position information, the system further analyzes and extracts key environmental parameters, such as Wi-Fi signal strength (RSSI), the number of visible networks, encryption type, etc. The system abstracts these parameters into higher-level scene features, such as "at home", "at the office", or "moving", providing input for subsequent scene recognition.

[0043] After obtaining the environmental characteristics, the system will accurately determine the current communication scenario through a scene recognition engine, which is usually based on a pre-set rule library, such as "if connected to a known company Wi-Fi and the signal is strong, the scenario is 'company stable'"; In order to prevent the scene from frequently switching due to signal fluctuations, the system also maintains a scene state machine, which requires new scene characteristics to meet for a period of time (such as 5 seconds) before being officially confirmed. The output of this step is a clear and structured scene identification that clearly defines the current communication environment, such as "company stable" or "mobile outdoor".

[0044] The system will construct a multi-factor decision matrix, considering three key dimensions: the currently determined communication scenario, the data to be transmitted from S111 (including its size, priority, and real-time requirement), and the real-time status of the device to be interacted (such as a cloud server); The decision logic will intelligently match these information, for example, in the "company stable" scenario, for regular sensor data, it will prefer to choose high-bandwidth, low-cost Wi-Fi; While in the "mobile outdoor" scenario, it switches to cellular network; The system will output a specific communication method decision, clearly specifying the protocol (such as MQTT), interface (such as Wi-Fi), and backup solution, ensuring the economy and reliability of data transmission.

[0045] Reference Figure 3 In step S12, the specific steps are:

[0046] S121: Collect the Internet of Things communication method, determine multiple project marks according to the detection of the Internet of Things communication method, and determine the corresponding sub-Internet of Things communication project according to the traceability of each project mark, to collect multiple sub-Internet of Things communication projects;

[0047] S122: Collect multiple communication parameters of the embedded device in each sub-Internet of Things communication project, determine the corresponding communication effect coefficient based on the response events of multiple communication parameters and multiple interaction data, and determine the first sub-communication path based on the project of each sub-Internet of Things communication project and the corresponding communication effect coefficient;

[0048] S123: Determine the second sub-communication path based on the project of each sub-Internet of Things communication project and the to-be-received data of the embedded device, and construct the communication path of the embedded device according to the first sub-communication path and the second sub-communication path.

[0049] In the embodiment of the present application, the Internet of Things communication method is collected, multiple project marks are determined according to the detection of the Internet of Things communication method, and the corresponding sub-Internet of Things communication project is determined according to the traceability of each project mark, to collect multiple sub-Internet of Things communication projects, which is compatible with the overall consideration of the traceability of each project mark, and ensures the accuracy of the corresponding sub-Internet of Things communication project.

[0050] At this time, the high-level communication decision (such as "use Wi-Fi for MQTT communication") output by S11 is converted into a series of structured tags that can be understood by the system; the parsing engine inside the system will query a predefined library of communication atomic operations based on this decision, and decompose the abstract target into multiple basic operation tags; each tag follows a unified syntax specification, such as WIFI_CONN (Wi-Fi connection) or MQTT_PUB (MQTT publish); the system will generate a preliminary tag set containing all necessary operations but not yet sorted, laying the foundation for subsequent dependency analysis.

[0051] The system analyzes the precedence and posteriority between each tag through a dependency backtracking algorithm, querying the internal dependency database; for example, performing MQTT_PUB (publish) must first complete MQTT_CONN (connection), and MQTT_CONN in turn depends on WIFI_CONN (Wi-Fi connection); based on these dependencies, the system will construct a directed acyclic graph (DAG) and generate a linear execution sequence that satisfies all dependency conditions through topological sorting; at the same time, the system will also attach priority, timeout time, retry count, and other key attributes to each sub-item in the sequence, making it a well-defined task unit.

[0052] The system constructs these sub-items with complete attributes and dependencies into a structured project list (such as a linked list or an array); the initial state of each sub-item in the list is set to "pending" (PENDING); this output list, as a clear and actionable execution blueprint, will be completely passed to S122 for specific path planning and parameter evaluation.

[0053] Specifically, the embedded device (lithium battery energy management device) receives the decision from S11: use Wi-Fi for MQTT communication; the parsing engine immediately starts, it identifies the two key parts of "Wi-Fi" and "MQTT", and extracts the corresponding tags from the atomic operation library; for "Wi-Fi", WIFI_SCAN (scan) and WIFI_CONN (connect) are generated; for "MQTT", MQTT_CONN (connect), MQTT_PUB (publish), and MQTT_SUB (subscribe) are generated; at this point, the system has obtained a preliminary tag set:

[0054] {WIFI_SCAN, WIFI_CONN, MQTT_CONN, MQTT_PUB, MQTT_SUB}.

[0055] The system begins to analyze the dependencies of these tags; by querying the dependency database, it determines the execution order: Wi-Fi must be scanned and connected before establishing an MQTT connection, and finally, message publishing or subscribing; based on this logic chain, the system constructs a directed acyclic graph and generates a basic execution sequence through topological sorting; at the same time, the system assigns execution attributes to each sub-project, such as marking WIFI_SCAN and WIFI_CONN as high priority and setting corresponding timeout and retry times to ensure timely reporting of critical data.

[0056] The system integrates these clearly defined and attribute complete sub-projects into a final list and initializes the status of all projects to "Pending"; the final sub-communication project list for the embedded device (lithium battery energy management device) is as follows: {tag: "WIFI_SCAN", status: PENDING,...};

[0057] {tag: "WIFI_CONN", status: PENDING, deps: ["WIFI_SCAN"],...};

[0058] {tag: "MQTT_CONN", status: PENDING, deps: ["WIFI_CONN"],...};

[0059] {tag: "MQTT_SUB", status: PENDING, deps: ["MQTT_CONN"],...};

[0060] {tag: "MQTT_PUB", status: PENDING, deps: ["MQTT_CONN"],...}.

[0061] This structured list provides a clear execution blueprint for S122, ensuring that the device can complete all operations from scanning the network to publishing battery status data step by step, stably and reliably; for example, the MQTT_PUB task will be used to publish real-time voltage, current, temperature, and health status (SOH) of the battery, while MQTT_SUB will be used to receive charging and discharging control instructions from the cloud.

[0062] Further, a plurality of communication parameters of the embedded device in each sub-thing communication project are collected, a corresponding communication effect coefficient is determined based on the plurality of communication parameters and the response events of the plurality of interaction data, and a first sub-communication path is determined based on the project of each sub-thing communication project and the corresponding communication effect coefficient, which is compatible with the overall consideration of the project of each sub-thing communication project and the corresponding communication effect coefficient, thereby ensuring the accuracy of the first sub-communication path.

[0063] At this time, the system will traverse the project list, trigger parameter collection tasks for each project (such as WIFI_CONN), and these parameters come from various sources, including RSSI (signal strength) and RTT (network delay) measured in real time through hardware drivers, static configurations (such as Wi-Fi passwords) read from non-volatile memory, and statistical data (such as average connection success rate) calculated from historical logs; all raw parameters will eventually be standardized into a unified data structure, forming a communication parameter vector associated with each sub-project, providing a data basis for subsequent quantitative evaluation.

[0064] The system will use a multi-factor weighted evaluation model, taking the communication parameter vector collected in the previous step and the interaction data attributes (such as packet size and real-time requirements) from S111 as input, and calculating a quantitative communication effect coefficient through a comprehensive formula. This formula dynamically adjusts the weights of different factors, and the output effect coefficient is a floating-point number. The higher the value, the better the expected effect of using the sub-project to complete the specific communication task under the current network conditions.

[0065] After obtaining the effect coefficient of each sub-project, the system will use the dependency graph constructed by S121 to replace each node with its corresponding effect coefficient, forming a weighted directed graph. The next task is to search for an optimal path from the starting node to the target node in this graph. Here, "optimal" usually refers to the highest comprehensive evaluation value of the effect coefficient of all nodes on the path. The system will use search algorithms such as Dijkstra and combine path pruning strategies to eliminate suboptimal paths. The output "first sub-communication path" is an ordered sequence of sub-projects, which represents the optimal operation sequence to complete the communication task under the current conditions.

[0066] Specifically, the main control MCU of the embedded device (lithium battery energy management device) queries various parameters from its communication coprocessor through a serial port; for the WIFI_CONN project, the coprocessor returns the current Wi-Fi signal strength (-45dBm), signal-to-noise ratio (35dB), and other information; for the MQTT_CONN project, the coprocessor measures the round-trip time (RTT) to the MQTT server through a TCP connection test, which is 50ms. In this way, each sub-project is associated with a detailed and quantitative communication parameter vector.

[0067] The system analyzes the data to be sent, which is a battery over-temperature warning event this time. Although such data packets are small, they have extremely high real-time and reliability requirements. Therefore, in the calculation model, the weights of latency and reliability are set to the highest, even higher than ordinary sensor data. Based on this, the system begins to calculate: for the WIFI_CONN item, since the RSSI and SNR are very good, the reliability score is extremely high, and after comprehensive calculation, the communication effect coefficient is 0.90 (slightly improved compared to the ordinary scene, because high reliability is highly valued); for the MQTT_CONN item, the 50ms RTT performs excellently for the high real-time requirement of the alarm, and the server is completely reachable, and the communication effect coefficient is as high as 0.95.

[0068] The system fills the calculated effect coefficient into the dependency graph, forming a weighted path: WIFI_SCAN>WIFI_CONN(0.90)>MQTT_CONN(0.95)>MQTT_PUB; the system evaluates the overall effect of this path and hypothetically evaluates the alternative cellular network path (assuming its effect coefficient is 0.78); after comparison, the Wi-Fi path is significantly superior to the cellular network in terms of latency and reliability; therefore, the first sub-communication path finally determined by the system is: WIFI_SCAN>WIFI_CONN>MQTT_CONN>MQTT_PUB, which is marked as the "optimal alarm uplink path" and will directly guide the embedded device to immediately perform network operations in this order to ensure that this critical battery over-temperature warning can be sent to the cloud in the fastest and most reliable way, triggering the corresponding safety policy.

[0069] Therefore, the second sub-communication path is determined based on the project of each sub-Internet of Things communication item and the to-be-received data of the embedded device, and the communication path of the embedded device is constructed according to the first sub-communication path and the second sub-communication path, which takes into account the overall consideration of the project of each sub-Internet of Things communication item and the to-be-received data of the embedded device, ensuring the accuracy of the communication path of the embedded device.

[0070] At this time, the system will analyze the task characteristics in the to-be-received data queue, such as data type (control instruction, configuration file, or firmware), size, reliability, and real-time requirement; then, a rule-based decision engine will select appropriate operations from the sub-item list of S121 according to these characteristics to construct a path specifically for receiving data; for example, for large file firmware download, the HTTP protocol is selected; while for small control instructions, the MQTT subscription function is used; the system generates one or more optimized second sub-communication paths.

[0071] The fusion algorithm identifies the common part of the two paths (such as a Wi-Fi connection) and merges them, setting branch points at appropriate nodes (such as after application layer connection establishment) to handle different uplink and downlink services; in addition, the algorithm also handles priority and resource competition issues between different branches, for example, when performing a high-bandwidth firmware download task, the system temporarily reduces the frequency of regular data reporting; the output structured path, like a communication state machine, can guide the device to intelligently and coordinately handle all communication tasks at runtime.

[0072] Specifically, assume that the cloud issues a new charging and discharging strategy configuration file (strategy_v3.json, about 5KB in size) to the embedded device; the system analyzes the task and determines that it is a small and medium-sized configuration file that requires high reliability and needs to be applied as soon as possible; the decision engine determines that although it can be downloaded through HTTP, considering its urgency and the MQTT connection established by the device, using MQTT_SUB (subscribe to a specific topic) to receive configuration push through MQTT is a more real-time solution; the system constructs a downlink path: WIFI_CONN>MQTT_CONN>MQTT_SUB.

[0073] The system needs to fuse two paths: the first sub-communication path (uplink):

[0074] WIFI_SCAN>WIFI_CONN>MQTT_CONN>MQTT_PUB (used for reporting battery status data); the second sub-communication path (downlink):

[0075] WIFI_CONN>MQTT_CONN>MQTT_SUB (used for receiving new strategy configuration).

[0076] The two paths completely coincide from WIFI_SCAN to MQTT_CONN; therefore, the starting part of the final path is merged into WIFI_SCAN>WIFI_CONN>MQTT_CONN; after the establishment of MQTT_CONN is successful, the path is differentiated into two parallel MQTT-based service branches; branch A is the regular service, which continuously reports battery voltage, current, temperature, etc. data through MQTT_PUB; branch B is the key service, which listens to the configuration update instructions issued by the cloud through MQTT_SUB.

[0077] The system sets a rule that when MQTT_SUB receives a new configuration file, it needs to be parsed and applied immediately; during this period, the system will temporarily suspend the MQTT_PUB task to ensure that CPU resources are fully focused on processing the new configuration, avoiding configuration application failure or delay due to data reporting interference; after the configuration application is successful, the MQTT_PUB task is restored.

[0078] The embedded device gets a complete and intelligent final communication path blueprint: the device establishes a network and an MQTT connection; after the connection is successful, two parallel tasks of data reporting (MQTT_PUB) and instruction listening (MQTT_SUB) are started at the same time; once a key configuration update is listened to, the system will prioritize the configuration processing, suspend data reporting, and then resume normal operation after processing is completed; through the design of S123, the embedded device can intelligently coordinate regular state reporting and key instruction receiving, ensuring the timeliness and reliability of the energy management strategy.

[0079] Reference Figure 4 In step S13, the specific steps are:

[0080] S131: Determine a plurality of communication nodes based on the detection of the communication path, and mark the node positions of each communication node, determine the first communication mode coefficient according to the node positions of each communication node and the network state of the embedded device;

[0081] S132: Determine the second communication mode coefficient according to the node form of each communication node and the network state of the embedded device, determine the final communication mode of the embedded device based on the first communication mode coefficient, the second communication mode coefficient and the mapping relationship of the second communication mode;

[0082] S133: Collect the interaction signal of the embedded device, determine the first heavy online communication content according to the interaction signal of the embedded device and the final communication mode; determine the second heavy online communication content according to the interaction signal of the embedded device and a plurality of communication parameters, determine the online communication event of the embedded device based on the first heavy online communication content and the second heavy online communication content.

[0083] In the embodiment of the present application, a plurality of communication nodes are determined based on the detection of the communication path, and the node positions of each communication node are marked, the first communication mode coefficient is determined according to the node positions of each communication node and the network state of the embedded device, which is compatible with the overall consideration of the node positions of each communication node and the network state of the embedded device, ensuring the accuracy of the first communication mode coefficient.

[0084] At this time, the system will analyze this path structure and identify each key network state or operation completion point in it, such as "Wi-Fi has been connected" or "MQTT session has been established"; then, the system will assign a hierarchical position mark (such as L2 representing the data link layer and L5 representing the application layer) to each identified node, thereby constructing an ordered and explicit hierarchical information communication node list, which lays a foundation for subsequent hierarchical evaluation.

[0085] After obtaining the list of communication nodes, the system begins to calculate the "first communication mode coefficient", which is mainly used to evaluate the basic carrying capacity of the communication link; the system will collect a series of network state parameters reflecting the health status of the physical and data link layers in real time through the underlying driver, such as the signal strength (RSSI) of Wi-Fi, signal-to-noise ratio (SNR) and physical rate; then, a weighted algorithm will map these parameters to an interval of [0, 1], where the weight will be dynamically adjusted according to the level of the node; the output coefficient is a quantitative value, the higher the value, the more stable the physical connection and the more reliable the underlying transmission, providing a solid foundation for the stable operation of the upper layer protocol.

[0086] Specifically, the embedded device (lithium battery energy management device) successfully performs WIFI_CONN and MQTT_CONN operations according to the final path of S12; the system detects that these operations have been completed and identifies them as key communication nodes; the path parser assigns level labels to these nodes: "Wi-Fi has been connected and IP has been obtained" is labeled as L2 (data link layer), and "MQTT session is active" is labeled as L5 (application layer); the embedded device generates an ordered list containing these two nodes.

[0087] In order to evaluate the Wi-Fi connection quality of the L2 node, the master MCU of the embedded device queries the current Wi-Fi status from its communication co-processor, obtaining the following parameters: RSSI is -42dBm, SNR is 38dB, physical rate is 65Mbps, and channel utilization is 15%; the system's evaluation model performs weighted calculation on these parameters: the signal strength of -42dBm and the signal-to-noise ratio of 38dB are both excellent, obtaining high scores; the rate of 65Mbps and the low channel utilization of 15% also perform excellently; after considering all factors, the system calculates the first communication mode coefficient as high as 0.94, which accurately indicates that the current Wi-Fi physical link quality of the embedded device is very good, providing a solid and reliable foundation for subsequent high-reliability battery status data reporting and immediate sending of critical alarm information.

[0088] Further, the second communication mode coefficient is determined according to the node form of each communication node and the network state of the embedded device, and the final communication mode of the embedded device is determined based on the mapping relationship between the first communication mode coefficient, the second communication mode coefficient and the second communication mode, which comprehensively considers the mapping relationship between the first communication mode coefficient, the second communication mode coefficient and the second communication mode, ensuring the accuracy of the final communication mode of the embedded device.

[0089] At this time, the system will analyze the form of the communication node, that is, the functional type and protocol characteristics of the node (such as the "publish / subscribe" mode of MQTT or the "request / response" mode of HTTP); the system will collect a series of performance indicators focusing on the network layer to the application layer, such as round-trip time (RTT), packet loss rate, and application layer response time; then, a weighted calculation model will dynamically adjust the weights of each indicator according to the node form, for example, for MQTT nodes, the weights of packet loss rate and application response time will be higher; the final output of the second communication mode coefficient is a numerical value that quantifies the end-to-end communication quality, which reflects the "service quality" of actual data exchange under the condition that the physical link is available.

[0090] The system will combine the "first communication mode coefficient" (basic bearing capacity) from S131 and the "second communication mode coefficient" (end-to-end efficiency) calculated in this step to form a complete evaluation of the current communication environment; then, the system will match this pair of coefficients with a pre-defined "communication mode mapping table", which presets the optimal communication strategy according to different coefficient interval combinations.

[0091] For example, when both coefficients are high, use MQTT with high QoS; when the basic link is good but the end-to-end efficiency is poor, switch to a more robust HTTP protocol; the system will output a specific, immediately executable final communication mode, which not only includes the interface and protocol, but also details parameters such as QoS level, security policy, etc.

[0092] Specifically, the embedded device (lithium battery energy management device) identifies the currently active MQTT_SESSION_ACTIVE node, which has a form of "publish / subscribe, supports QoS"; in order to evaluate its end-to-end efficiency, the device sends a test message to the MQTT Broker and measures the application layer response time as 80ms, while the recent packet loss rate is 0%; since the energy management business has very high requirements for data reliability, the model gives the highest weight to response time and packet loss rate; both the 80ms response time and the 0% packet loss rate perform excellently, so the system calculates the second communication mode coefficient as high as 0.92.

[0093] The system combines two key coefficients: the first communication mode coefficient from S131 is 0.85 (basic bearing capacity is good), and the second communication mode coefficient calculated in this step is 0.92 (end-to-end efficiency is excellent); the system matches this pair of coefficients (0.85, 0.92) with the internal communication mode mapping table; although the basic link (0.85) does not reach the "excellent" standard, the end-to-end efficiency (0.92) performs outstandingly; considering the rigid demand for data confirmation of the energy management business, the strategy of the mapping table still tends to use the most reliable MQTT.

[0094] Therefore, the system finally decides to adopt the communication mode of "Wi-Fi + MQTT (QoS1)", which means that although the physical signal is not perfect, the end-to-end interaction quality is very high, and the system judges that the MQTT communication of the highest reliability level can be supported, so as to ensure that each critical battery status data or alarm information can be reliably confirmed by the cloud, and the safety of energy management is maximized.

[0095] Therefore, the interaction signal of the embedded device is collected, the first online communication content is determined according to the interaction signal of the embedded device and the final communication mode, and the second online communication content is determined according to the interaction signal of the embedded device and the plurality of communication parameters. The online communication event of the embedded device is determined based on the first online communication content and the second online communication content, which is compatible with the overall consideration of the first online communication content and the second online communication content, and ensures the accuracy of the online communication event of the embedded device. At the same time, the communication path of the embedded device is introduced, which is compatible with the overall consideration of the final communication mode, the interaction signal of the embedded device and the corresponding plurality of communication parameters, and realizes the accuracy of the online communication event of the embedded device.

[0096] At this time, the system will receive the interaction signal triggering the communication (such as sensor reading exceeding the standard), and combine the final communication mode determined in S132 (such as MQTT QoS1) to encapsulate according to the business logic. This process includes formatting the original data into a standard structure such as JSON, and determining the target address (such as MQTT topic) and service quality level according to the protocol and strategy; the final output of the "first content" is a complete application-oriented business data packet, which clearly states "what to say" and "according to which business rule to say", but has not been encoded into a bottom protocol frame.

[0097] The system will construct a complete protocol data unit (PDU) according to the specific communication protocol specification, taking the first content as the payload, which includes adding the correct frame header, filling the parameter field (such as QoS level, target topic identifier), embedding the payload, and calculating the check value to ensure the integrity; the final output of the "second content" is a binary protocol frame sequence, which focuses on "what physical format to say", which is the final physical form of communication.

[0098] The system will bind the first (business logic) and second (protocol implementation) contents to create a complete "online communication event" object, which not only contains the binary frame to be sent, but also includes its business context information such as event ID, timestamp, retry strategy, timeout setting, and callback function after success or failure. This complete event is placed in the sending queue and waits for the dispatcher to execute, thereby realizing a complete closed loop from business intent to physical transmission, and providing all the context for subsequent processing.

[0099] Specifically, when the embedded device (lithium battery energy management device) detects that the cell temperature reaches 65°C, exceeding the safety threshold, the system combines this signal with the communication mode of "Wi-Fi+MQTT (QoS1)"; the system encapsulates it into a "cell overtemperature" safety alarm with the highest priority, generates a JSON format service data packet:

[0100] {"deviceId":"BMS_001","alertType":"cell_overtemp","maxTemp":65,"status":"critical",...};According to the MQTT strategy, the target topic is determined to be / battery / 1 / critical_alert, which forms the first content, a service data packet containing the target, payload and QoS level.

[0101] The system protocol encodes this service data packet; it selects a custom MQTX frame header, and fills in the publish instruction, target topic identifier and QoS level 1 in the parameter field; embeds the JSON string of the previous step as the payload, and calculates the CRC16 checksum value and frame tail XQTM; a complete binary protocol frame is constructed, which is the physical data that can be directly delivered to the hardware driver for sending.

[0102] The system integrates the first two contents into a complete communication event object, which not only contains the binary frame just generated, but also binds the business context, such as event ID, more aggressive retry strategy (up to 5 times, shorter backoff interval), shorter timeout time (2 seconds) and callback function of processing result. This complete event is placed in the highest priority of the sending queue, and the communication scheduler of the embedded device will immediately take it out, send it to the communication coprocessor through the serial port, and call the corresponding callback function according to the execution result, so as to ensure that this critical safety alarm can be delivered to the cloud in the fastest and most reliable way.

[0103] Reference Figure 5 In step S14, the specific steps are:

[0104] S141: Real-time monitoring of online communication of embedded devices, and collecting corresponding online communication processes, determining a plurality of sub-exceptional communication regions based on detection of the online communication processes, and determining corresponding abnormal communication nodes according to the region position, corresponding region form and abnormal communication content of each sub-exceptional communication region;

[0105] S142: Collecting a plurality of abnormal communication nodes, and determining a communication abnormality combination according to the node position of each abnormal communication node and the corresponding communication range in the communication path;

[0106] S143: determining an online communication combination according to the node position of each abnormal communication node and the online communication event, determining a corresponding communication maintenance event according to the communication abnormal combination, the online communication combination and the past maintenance event of the embedded device.

[0107] In the embodiments of the present application, the online communication of the embedded device is monitored in real time, and the corresponding online communication process is collected, a plurality of sub-abnormal communication areas are determined based on the detection of the online communication process, and a corresponding abnormal communication node is determined according to the area position, the corresponding area form and the abnormal communication content of each sub-abnormal communication area. The overall consideration of the area position, the corresponding area form and the abnormal communication content of each sub-abnormal communication area is compatible, and the accuracy of the corresponding abnormal communication node is ensured.

[0108] At this time, the system continuously tracks the life cycle of each active communication event through a high-priority background task; it collects and maintains a process table, which records the key performance indicators (KPIs) of each event, such as current state, timestamp, retry count, transmission delay and error count, etc. This process provides real-time, quantitative data basis for subsequent anomaly detection.

[0109] After obtaining real-time process data, the system compares it with preset static or dynamic thresholds, and once the KPIs exceed the thresholds, it triggers anomaly detection; then, the system classifies abnormal events into different “sub-abnormal communication areas” according to their sources and nature. These areas are divided according to the hierarchy and functional modules of the network protocol stack, such as physical and link layer areas, network and transport layer areas, application protocol areas, etc., thus forming a preliminary fault classification system.

[0110] The system integrates three aspects of information: the protocol stack level where the abnormal area is located, the mode of abnormal performance (such as continuous interruption or intermittent jitter), and the specific communication content that triggered the anomaly; through this multi-dimensional information fusion, the system can instantiate an abstract “area” into a specific, context-specific “abnormal communication node”. This node is the smallest diagnosable unit of the fault, and the list it produces contains rich diagnostic information, providing accurate input for subsequent fault pattern analysis.

[0111] Specifically, the embedded device (lithium battery energy management device) detects that the battery cell is overheated, immediately sends a highest priority "battery cell overheating" safety warning message (event evt_77491) to the cloud; the communication state monitor records the event state as "sending", and starts a 2-second confirmation waiting timer (shorter than ordinary data); after 2 seconds, since no confirmation (PUBACK) is received from the cloud, the monitor updates the event state to "waiting for confirmation", the retry counter is incremented by 1, and immediately resends; this process is repeated 5 times (more times than ordinary data).

[0112] After the 5th retry still fails, the retry counter of the event evt_77491 reaches the preset maximum threshold 5; the monitor immediately triggers a highest level abnormality detection event; the system analyzes the abnormality and finds that the failure occurs in the waiting for MQTT protocol layer confirmation stage, so it preliminarily classifies the fault into the "application protocol area".

[0113] The system starts accurate positioning; it fuses three aspects of information: the abnormal area is located at L5 (application layer), the abnormality is manifested as "sustained interruption" of 5 consecutive retry failures, and the specific content of the failure is publishing a safety warning to the / battery / 1 / critical_alert topic with QoS of 1; through fusion analysis, the system instantiates a specific abnormal communication node; the finally output node clearly points out that the problem is "MQTTBroker confirmation timeout", and the problem persists, affecting the transmission of critical safety alerts. This accurate and high-priority diagnosis result will be immediately transmitted to S142 to trigger a higher level of emergency fault recovery mode.

[0114] Further, a plurality of abnormal communication nodes are collected, and a communication abnormality combination is determined according to the node positions of the abnormal communication nodes and the corresponding communication ranges in the communication paths, which is compatible with the overall consideration of the node positions of the abnormal communication nodes and the corresponding communication ranges in the communication paths, and ensures the accuracy of the communication abnormality combination.

[0115] At this time, the system will collect all abnormal communication nodes output by S141, and perform deduplication and normalization processing to merge repeated or similar nodes while preserving the accurate timestamps of each node; finally, a structured and non-duplicate abnormal node list is output, which represents all communication faults encountered by the device in the current time period, providing a complete data set for subsequent pattern analysis.

[0116] The system maps the nodes to predefined logical communication ranges (L1-L5) such as "physical link range", "network access range", or "upper service range" according to their locations. By analyzing which ranges have abnormal nodes, the system can identify macro communication abnormal combination patterns. For example, if the abnormality is concentrated in the bottom range, it is "bottom link collapse"; if only the upper service is abnormal and the bottom is normal, it is "upper service interruption". This process elevates scattered fault points to strategic level fault classification, providing a clear basis for subsequent maintenance decisions.

[0117] Specifically, assume that the embedded device (lithium battery energy management device) encounters MQTT_BROKER_ACK_TIMEOUT failure when sending "cell over-temperature" safety alarm; At the same time, as part of the heartbeat mechanism, the system attempts to report the regular battery voltage data to the cloud through HTTP, which also fails; S141 generates two abnormal nodes: one is MQTT_BROKER_ACK_TIMEOUT located at L5, and the other is HTTP_REQUEST_TIMEOUT also located at L5; The system aggregates these two nodes to form an abnormal node list containing two L5 layer faults.

[0118] The system starts analyzing this node list; it maps both nodes to "upper service range"; then, the system checks the status of the bottom range and finds that the nodes representing Wi-Fi connection and IP acquisition are all normal. This "bottom normal, multiple upper service abnormal" pattern exactly matches the predefined "upper service interruption" combination pattern.

[0119] The conclusion produced by S142 is that the communication abnormal combination is "upper service interruption", and the root cause is network gateway failure or DNS resolution problem. This conclusion is crucial for energy management devices, as it means that both critical safety alarms and regular heartbeat data cannot reach the cloud, and the system must immediately activate the highest level of emergency communication plan, such as enabling the backup 4G / 5G cellular communication module to ensure uninterrupted connection with the cloud.

[0120] Therefore, according to the node location of each abnormal communication node and the online communication event, the online communication combination is determined, and according to the communication abnormal combination, the online communication combination and the past maintenance events of the embedded device, the corresponding communication maintenance event is determined, which is compatible with the overall consideration of the communication abnormal combination, the online communication combination and the past maintenance events of the embedded device, and ensures the accuracy of the corresponding communication maintenance event.

[0121] At this time, the system will associate the "fault" (abnormal communication node) identified by S141 with the "behavior" (online communication event) generated by S133 in terms of time and logic; by analyzing the business being executed by the device when the fault occurs, the system can identify different online communication combination patterns.

[0122] A decision engine will integrate three aspects of information: macro "communication abnormal combination" from S142, "online communication combination" from this step, and "past maintenance events" in the historical database; through a decision tree or machine learning model, the system will comprehensively judge the pattern of the current fault, business impact, and historical experience, and thus match the best maintenance strategy; the final output "communication maintenance event" is a specific and executable instruction, which not only solves the current problem, but also takes into account business impact and historical effectiveness, achieving adaptive fault recovery.

[0123] Specifically, the system checks the timestamps and finds that the MQTT_BROKER_ACK_TIMEOUT node is generated when executing the highest priority "battery over-temperature" safety alarm publishing event, while the HTTP_REQUEST_TIMEOUT node is generated when executing the regular battery voltage heartbeat reporting event; since the "battery over-temperature" alarm is directly related to battery safety and belongs to the highest level of critical business, the system identifies the current online communication combination as "key business interruption".

[0124] The intelligent decision engine begins to integrate information for judgment; it inputs three key information: the communication abnormal combination is "upper layer service interruption", the online communication combination is "key business interruption" (and is safety related), and the historical database shows that similar faults are eventually solved by "restarting the gateway"; based on the extreme severity of safety alarm communication failure and historical experience, the engine decides to skip all invalid intermediate attempts (such as MQTT reconnection) and directly execute the most decisive and effective solution.

[0125] The system generates a specific communication maintenance event: instructing the embedded device to immediately send a restart instruction to the company gateway through a backup channel (such as a 4G / 5G module or a local Bluetooth), and at the same time, through the backup channel, report this communication failure and gateway restart operation as a new highest priority alarm to the cloud, which fully embodies the intelligence and decisiveness of the system in handling safety critical business.

[0126] Reference Figure 6 In step S15, the specific steps are:

[0127] S151: collect the communication maintenance event, determine a plurality of sub-communication maintenance measures based on the identification of the communication maintenance event, at the same time, collect the online communication process of the embedded device, determine the first heavy multi-dimensional communication content according to the plurality of sub-communication maintenance measures and the online communication process of the embedded device;

[0128] S152: real-time monitoring of the embedded device to be received data, and determining the second heavy multi-dimensional communication content according to the plurality of sub-communication maintenance measures and the embedded device to be received data, determining the multi-dimensional communication system of the embedded device based on the training of the first heavy multi-dimensional communication content and the second heavy multi-dimensional communication content;

[0129] S153: collect a plurality of data load parameters of the embedded device, determine the data load state of the embedded device according to the plurality of data load parameters and the current working state of the embedded device, and determine the first dynamic communication coefficient according to the multi-dimensional communication system of the embedded device and the data load state of the embedded device;

[0130] S154: determine the second dynamic communication coefficient according to the multi-dimensional communication system of the embedded device and the service life of the embedded device; determine the dynamic communication event of the embedded device based on the mapping relationship of the first dynamic communication coefficient, the second dynamic communication coefficient and the dynamic communication event.

[0131] In the embodiment of the application, the communication maintenance event is collected, the plurality of sub-communication maintenance measures are determined based on the identification of the communication maintenance event, at the same time, the online communication process of the embedded device is collected, the first heavy multi-dimensional communication content is determined according to the plurality of sub-communication maintenance measures and the online communication process of the embedded device, which is compatible with the overall consideration of the plurality of sub-communication maintenance measures and the online communication process of the embedded device, and ensures the accuracy of the first heavy multi-dimensional communication content.

[0132] At this time, the system receives the communication maintenance event (such as "restarting the gateway") from S143, and decomposes it into an ordered sub-communication maintenance measure list (such as establishing a backup channel, authentication, sending instructions, etc.) by querying the built-in "measure knowledge base"; each sub-measure will be assigned with attributes such as estimated execution time, required resources, etc. This process refines a macro maintenance target into a structured and manageable operation plan.

[0133] The system takes a snapshot of the current online communication process (such as the sending queue state, resource occupancy rate) before performing maintenance; it comprehensively considers "what maintenance to do" (sub-measure list) and "what is currently being done" (process snapshot) to formulate a dynamic, multi-dimensional communication management strategy, which determines from three dimensions of resource arbitration, task scheduling and business continuity how the maintenance task and the existing business coexist, such as whether to suspend normal business, how to handle the interrupted data, etc.; the final output of the "first multi-dimensional communication content" is a temporary runtime strategy configuration for guiding the device to intelligently coordinate various tasks during maintenance.

[0134] Further, the real-time monitoring of the embedded device's to-be-received data, and determining the second multi-dimensional communication content according to the plurality of sub-communication maintenance measures and the to-be-received data of the embedded device, determining the multi-dimensional communication system of the embedded device based on the training of the first multi-dimensional communication content and the second multi-dimensional communication content, compatible with the overall consideration of the training of the first multi-dimensional communication content and the second multi-dimensional communication content, ensures the accuracy of the multi-dimensional communication system of the embedded device.

[0135] At this time, the system will continuously monitor all downlink data channels, and according to the needs of the maintenance task, formulate a coordination strategy, which starts from three dimensions of access control, data classification processing and security, determines whether to allow new connections, how to process incoming data (such as immediate processing, caching or rejection), and whether to need to enhance security verification; the final output of the "second multi-dimensional communication content" is a temporary runtime strategy, which ensures that the device can respond to critical instructions during maintenance, and avoid unnecessary interference and security risks.

[0136] The system intelligently fuses the "uplink / interior management strategy" generated by S151 and the "downlink / external interaction strategy" generated by this step through a strategy fusion engine; the engine will detect and solve potential conflicts between the two strategy sets, for example, when the resource conservation requirement conflicts with the urgent instruction receiving requirement, safety will be prioritized; the fused strategy is instantiated as a complete, dynamic "multi-dimensional communication system", which fully takes over communication management and ensures the balance between maintenance tasks, business continuity and system security.

[0137] Further, a plurality of data load parameters of the embedded device are collected, the data load state of the embedded device is determined according to the plurality of data load parameters and the current working state of the embedded device, and the first dynamic communication coefficient is determined according to the multi-dimensional communication system of the embedded device and the data load state of the embedded device, which is compatible with the overall consideration of the multi-dimensional communication system of the embedded device and the data load state of the embedded device, ensuring the accuracy of the first dynamic communication coefficient.

[0138] At this time, the system will collect a series of multi-dimensional load parameters in real time, such as CPU utilization, memory occupancy, task scheduling delay, and buffer level; through a load evaluation model, these parameters are fused into a quantitative data load state level (such as IDLE, NORMAL, HIGH, OVERLOADED), which provides a key internal state basis for subsequent communication strategy adjustment.

[0139] The system will combine the current "data load state" and the "multi-dimensional communication system" determined by S152, through a dynamic coefficient calculation model, to evaluate the "ability margin" of the device executing the current communication strategy; the final output "first dynamic communication coefficient" is a value between 0 and 1, which dynamically quantifies the "health" and "reliability" of the current communication task of the device; the higher the coefficient, the more reliable the communication; the lower the coefficient, the higher the risk of communication failure due to internal resource shortage; this coefficient will be used for subsequent adaptive decision-making, so that the communication strategy can respond to changes in the internal state of the device in real time.

[0140] Therefore, the second dynamic communication coefficient is determined according to the multi-dimensional communication system of the embedded device and the service life of the embedded device; the dynamic communication event of the embedded device is determined based on the mapping relationship between the first dynamic communication coefficient, the second dynamic communication coefficient, and the dynamic communication event, which takes into account the overall consideration of the mapping relationship between the first dynamic communication coefficient, the second dynamic communication coefficient, and the dynamic communication event, ensuring the accuracy of the dynamic communication event of the embedded device, while introducing the communication maintenance event to further control the multi-dimensional communication system, realizing the overall consideration of the multi-dimensional communication system of the embedded device, the data load state of the embedded device, and the service life of the embedded device, and improving the accuracy of the dynamic communication event of the embedded device.

[0141] At this time, the system will analyze the risk level of the current communication system (such as normal mode, maintenance mode, or OTA mode), and combine the service life of the device to calculate a hardware aging factor; through an aging model, the system will fuse these two factors to generate a "second dynamic communication coefficient", which is a forward-looking indicator reflecting the communication reliability based on hardware aging and long-term wear and tear; the lower the coefficient, the higher the long-term risk to the hardware caused by executing the current task.

[0142] The system fuses the first dynamic communication coefficient (reflecting instantaneous capability margin) generated by S153 and the second dynamic communication coefficient (reflecting long-term health degree) generated by this step; through inquiring a preset dynamic communication event mapping table, according to the combination of the two coefficients, the final specific dynamic communication event is matched out, which is according to the plan, degraded service, delayed task or enters the safety mode, so as to realize the fine, intelligent and preventive management of the communication behavior.

[0143] Please refer to Figure 7 , Figure 7 It is a structural composition schematic view of a communication system of an embedded device based on Internet of Things communication in the embodiment of the application; the communication system of the embedded device based on Internet of Things communication comprises:

[0144] The Internet of Things communication mode module 21 is configured to determine a corresponding data interaction space based on a database of the embedded device, determine an Internet of Things communication mode of the embedded device according to a plurality of interaction data of the data interaction space of the embedded device and a current position of the embedded device;

[0145] The communication path module 22 is configured to determine a plurality of sub Internet of Things communication items according to the identification of the Internet of Things communication mode, determine a communication path of the embedded device based on item content of each sub Internet of Things communication item and data to be received by the embedded device;

[0146] The online communication event module 23 is configured to determine a final communication mode of the embedded device based on a node form of a plurality of communication nodes of the communication path and a network state of the embedded device, determine an online communication event of the embedded device based on the final communication mode, an interaction signal of the embedded device and a plurality of corresponding communication parameters;

[0147] The communication maintenance event module 24 is configured to determine a plurality of abnormal communication nodes based on detection of the online communication process, determine a communication maintenance event according to a node position of each abnormal communication node, a corresponding communication range in the communication path and the online communication event;

[0148] The dynamic communication event module 25 is configured to determine a multi-dimensional communication system of the embedded device according to a plurality of sub communication maintenance measures of the communication maintenance event, an online communication process of the embedded device and a communication progress of the data to be received by the embedded device, determine a dynamic communication event of the embedded device according to the multi-dimensional communication system of the embedded device, a data load state of the embedded device and a service life of the embedded device.

[0149] Any combination of the technical features of the above embodiments is possible, in order to make the description simple, not all combinations of the technical features in the above embodiments are described, however, as long as the combination of the technical features does not exist contradictory, it should be considered that it is within the scope of the present application.

Claims

1. A communication method of an embedded device based on Internet of Things communication, characterized by, The method comprises the following steps: determining a corresponding data interaction space based on an embedded device database, determining an Internet of Things communication mode of the embedded device according to multiple interaction data of the data interaction space of the embedded device and a current position of the embedded device; determining multiple sub-Internet of Things communication projects according to the identification of the Internet of Things communication mode, determining a communication path of the embedded device based on the project content of each sub-Internet of Things communication project and the to-be-received data of the embedded device; determining a final communication mode of the embedded device based on the node form of multiple communication nodes of the communication path and the network state of the embedded device; determining an online communication event of the embedded device based on the final communication mode, the interaction signal of the embedded device and the corresponding multiple communication parameters; determining multiple abnormal communication nodes based on the detection of the online communication process, determining a communication maintenance event according to the node position of each abnormal communication node, the corresponding communication range in the communication path and the online communication event; determining a multi-dimensional communication system of the embedded device according to multiple sub-communication maintenance measures of the communication maintenance event, the online communication process of the embedded device and the communication progress of the to-be-received data of the embedded device, determining a dynamic communication event of the embedded device according to the multi-dimensional communication system of the embedded device, the data load state of the embedded device and the service life of the embedded device.

2. The method of claim 1, wherein, The method comprises the following steps: collecting the database of the embedded device, determining multiple data spaces according to the traversal of the database of the embedded device, determining a corresponding data interaction space based on the identification of the multiple data spaces, monitoring the data interaction space in real time, and determining multiple interaction data according to the matching of the data interaction space and the embedded device; collecting the current position of the embedded device, determining multiple environmental parameters and scene features according to the detection of the current position of the embedded device, determining the current communication scene of the embedded device according to the multiple environmental parameters and scene features, and determining the Internet of Things communication mode of the embedded device based on the current communication scene of the embedded device, the multiple interaction data and the working state of the to-be-interacted device.

3. The method of claim 1, wherein, The method comprises the following steps: collecting the Internet of Things communication mode, determining multiple project markers according to the detection of the Internet of Things communication mode, determining a corresponding sub-Internet of Things communication project according to the tracing of each project marker, and collecting multiple sub-Internet of Things communication projects; collecting multiple communication parameters of the embedded device in each sub-Internet of Things communication project, determining a corresponding communication effect coefficient based on the response event of the multiple communication parameters and the multiple interaction data, and determining a first sub-communication path based on the project of each sub-Internet of Things communication project and the corresponding communication effect coefficient; Determine a second sub-communication path based on the data to be received by the project and the embedded device of each sub-Internet of Things communication project, and construct a communication path of the embedded device according to the first sub-communication path and the second sub-communication path.

4. The method of claim 1, wherein, Determine the final communication mode of the embedded device based on the node form of the multiple communication nodes of the communication path and the network state of the embedded device; Determine the online communication event of the embedded device based on the final communication mode, the interaction signal of the embedded device, and the corresponding multiple communication parameters, including: Determine multiple communication nodes based on the detection of the communication path, mark the node positions of each communication node, and determine the first communication mode coefficient according to the node positions of each communication node and the network state of the embedded device; Determine the second communication mode coefficient according to the node form of each communication node and the network state of the embedded device, and determine the final communication mode of the embedded device based on the mapping relationship between the first communication mode coefficient, the second communication mode coefficient, and the second communication mode.

5. The method of claim 4, wherein, Determine the final communication mode of the embedded device based on the node form of the multiple communication nodes of the communication path and the network state of the embedded device; Determine the online communication event of the embedded device based on the final communication mode, the interaction signal of the embedded device, and the corresponding multiple communication parameters, including: Collect the interaction signal of the embedded device, and determine the first online communication content according to the interaction signal of the embedded device and the final communication mode; Determine the second online communication content according to the interaction signal of the embedded device and the multiple communication parameters, and determine the online communication event of the embedded device based on the first online communication content and the second online communication content.

6. The method of claim 1, wherein, Determine multiple abnormal communication nodes based on the detection of the online communication process, and determine the communication maintenance event according to the node position of each abnormal communication node, the corresponding communication range in the communication path, and the online communication event, including: Real-time monitor the online communication of the embedded device, collect the corresponding online communication process, determine the corresponding multiple sub-abnormal communication areas based on the detection of the online communication process, and determine the corresponding abnormal communication nodes according to the area position of each sub-abnormal communication area, the corresponding area form, and the abnormal communication content.

7. The method of claim 6, wherein the method further comprises: Determine multiple abnormal communication nodes based on the detection of the online communication process, and determine the communication maintenance event according to the node position of each abnormal communication node, the corresponding communication range in the communication path, and the online communication event, including: Collect multiple abnormal communication nodes, determine the communication abnormal combination according to the node position of each abnormal communication node and the corresponding communication range in the communication path; Determine the online communication combination according to the node position of each abnormal communication node and the online communication event, and determine the corresponding communication maintenance event according to the communication abnormal combination, the online communication combination, and the past maintenance event of the embedded device.

8. The method of claim 1, wherein, The process involves determining a multi-dimensional communication system for the embedded device based on multiple sub-communication maintenance measures of communication maintenance events, the online communication process of the embedded device, and the communication progress of the data to be received by the embedded device. Dynamic communication events for the embedded device are then determined based on this multi-dimensional communication system, the data load status of the embedded device, and the service life of the embedded device. These events include: The system collects communication maintenance events, determines multiple sub-communication maintenance measures based on the identification of these events, and simultaneously collects the online communication process of the embedded device. Based on the multiple sub-communication maintenance measures and the online communication process of the embedded device, the system determines the first layer of multi-dimensional communication content. The system monitors the data to be received by the embedded device in real time, and determines the second layer of multi-dimensional communication content based on multiple sub-communication maintenance measures and the data to be received by the embedded device. Based on the training of the first layer of multi-dimensional communication content and the second layer of multi-dimensional communication content, the system determines the multi-dimensional communication system of the embedded device.

9. The method of claim 8, wherein, The process of determining a multi-dimensional communication system for an embedded device based on multiple sub-communication maintenance measures of communication maintenance events, the online communication process of the embedded device, and the communication progress of the data to be received by the embedded device, and determining dynamic communication events for the embedded device based on the multi-dimensional communication system, the data load status of the embedded device, and the service life of the embedded device, further includes: Collect multiple data load parameters of the embedded device, determine the data load state of the embedded device based on the multiple data load parameters and the current working state of the embedded device, and determine the first dynamic communication coefficient based on the multi-dimensional communication system of the embedded device and the data load state of the embedded device. The second dynamic communication coefficient is determined based on the multi-dimensional communication system of the embedded device and the service life of the embedded device; the dynamic communication events of the embedded device are determined based on the mapping relationship between the first dynamic communication coefficient, the second dynamic communication coefficient and the dynamic communication events.

10. A communication system for an embedded device based on Internet of Things communication, characterized in that, The communication system of the embedded device based on Internet of Things (IoT) communication is applied to the communication method of the embedded device based on IoT communication as described in any one of claims 1-9, wherein the communication system of the embedded device based on IoT communication includes: The IoT communication module is used to determine the corresponding data interaction space based on the database of the embedded device, and to determine the IoT communication mode of the embedded device based on multiple interaction data in the data interaction space of the embedded device and the current position of the embedded device. The communication path module is used to determine multiple sub-IoT communication items based on the identification of the IoT communication method, and to determine the communication path of the embedded device based on the item content of each sub-IoT communication item and the data to be received by the embedded device. The online communication event module is used to determine the final communication method of the embedded device based on the node configuration of multiple communication nodes in the communication path and the network status of the embedded device; and to determine the online communication event of the embedded device based on the final communication method, the interaction signals of the embedded device, and the corresponding multiple communication parameters. The communication maintenance event module is configured to determine a plurality of abnormal communication nodes based on the detection of the online communication process, determine a communication maintenance event based on the node position of each abnormal communication node, the corresponding communication range in the communication path, and the online communication event; The dynamic communication event module is configured to determine a multi-dimensional communication system of the embedded device based on a plurality of sub-communication maintenance measures of the communication maintenance event, the online communication process of the embedded device, and the communication progress of the data to be received by the embedded device, and determine a dynamic communication event of the embedded device based on the multi-dimensional communication system of the embedded device, the data load state of the embedded device, and the service life of the embedded device.

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