Intelligent sorting terminal and cloud data synchronization method and system

Abstract

The invention provides an intelligent sorting terminal and cloud data synchronization method and system. The method comprises the following steps: receiving state updating information of the intelligent sorting terminal, performing analysis processing, and generating a terminal state snapshot; on the basis of the terminal state snapshot, the difference between the cloud storage task template and the current task progress is finely analyzed by applying an increment synchronization algorithm, and a real-time difference detection technology is adopted to perform precise processing to generate the latest working state of the terminal; based on the latest working state of the terminal, performing encryption processing by applying a secure transmission algorithm under a zero-trust architecture, and finishing updating processing through a preset secure channel by adopting a multi-path transmission technology to generate an updated local data state; and based on the updated local data state, feeding back confirmation information to the cloud, evaluating and adjusting task allocation and resource configuration of the intelligent sorting terminal, and generating a data synchronization strategy. According to the technical scheme provided by the invention, efficient and safe data synchronization is realized, and the terminal is ensured to be always in the optimal working state.

Description

Technical Field

[0001] The embodiments of the present application relate to the field of cloud computing technology, and more particularly to a method and system for synchronizing data between an intelligent sorting terminal and a cloud. Background Art

[0002] With the rapid development of the Internet of Things and cloud computing technologies, terminals need to receive and parse status update information to understand the specific needs and current working status of each terminal and generate a snapshot of the terminal status. Based on this snapshot, the system must be able to carefully analyze the differences between the task templates stored in the cloud and the current task progress of the terminal, identify the data items that need to be updated, and use real-time difference detection technology for precise processing to adapt to the latest working status. In addition, in order to ensure the security and reliability of data transmission, the system also needs to have strict access control, identity authentication mechanism, and multi-path transmission capabilities to generate updated local data status. Finally, the system should be able to feedback confirmation information to the cloud, evaluate and adjust the task allocation and resource allocation of the intelligent sorting terminal, and generate an optimized data synchronization strategy.

[0003] At present, common intelligent sorting terminals and cloud data synchronization solutions mainly include full synchronization and simple incremental synchronization. Full synchronization transmits all data each time. Although it ensures data consistency, it will cause a large amount of redundant data transmission, increase bandwidth usage and processing time. Simple incremental synchronization only transmits changed data, which improves synchronization efficiency, but it is easy to miss some changes in complex environments, resulting in data inconsistency. In addition, most existing solutions lack strict security measures and cannot effectively deal with the risks of network attacks and data leakage, especially during the transmission of sensitive data.

[0004] Existing solutions have obvious deficiencies in some aspects. First, the full synchronization method transmits a large amount of redundant data, which not only wastes precious network bandwidth resources, but also prolongs the synchronization time, affects the system's response speed, and lacks data synchronization efficiency and security; secondly, although simple incremental synchronization improves efficiency, it is prone to data omissions and inconsistencies in complex application scenarios, reducing the reliability and accuracy of the system. More importantly, existing solutions generally lack a complete security mechanism and are difficult to resist potential network attacks and data leakage risks, especially when sensitive data is involved, which seriously affects the overall security of the system. Therefore, there is an urgent need for a new method that can both improve synchronization efficiency and ensure data transmission security. Summary of the invention

[0005] The embodiments of the present application provide a method and system for synchronizing data between an intelligent sorting terminal and a cloud, so as to solve the problems of insufficient data synchronization efficiency and security in the prior art.

[0006] In a first aspect, an embodiment of the present application provides a method for synchronizing data between an intelligent sorting terminal and a cloud, comprising:

[0007] Receive status update information of intelligent sorting terminals, parse and process it to understand the specific requirements and current working status of each terminal, and generate a terminal status snapshot;

[0008] Based on the terminal status snapshot, the incremental synchronization algorithm is used to carefully analyze the difference between the cloud storage task template and the current task progress, identify the data items that need to be updated, and use real-time difference detection technology to perform precise processing to adapt to the latest working status and generate the latest working status of the terminal;

[0009] Based on the latest working status of the terminal, the secure transmission algorithm under the zero-trust architecture is used for encryption processing, strict access control and identity authentication mechanisms are implemented during data transmission, and multi-path transmission technology is used to send the data to the corresponding intelligent sorting terminal. The update processing is completed through the preset secure channel to generate an updated local data status;

[0010] Based on the updated local data status, the confirmation information is fed back to the cloud, the task allocation and resource configuration of the intelligent sorting terminal are evaluated and adjusted, and a data synchronization strategy is generated.

[0011] Optionally, based on the terminal status snapshot, an incremental synchronization algorithm is used to perform a detailed analysis of the difference between the cloud storage task template and the current task progress, identify the data items to be updated, and use real-time difference detection technology to perform precise processing to adapt to the latest working status and generate the latest working status of the terminal, including:

[0012] Based on the terminal status snapshot, the cloud storage task template is compared with the current task progress of the intelligent sorting terminal to generate an initial difference report;

[0013] Based on the initial difference report, an incremental synchronization algorithm is used to conduct an in-depth analysis of the differences between the cloud storage task template and the current task progress of the intelligent sorting terminal, identify the data items that need to be updated, improve synchronization efficiency, and generate a list of data that needs to be updated;

[0014] Based on the list of data to be updated, real-time difference detection technology is used to perform precise processing to avoid repeated and redundant data transmission and generate a precise data set to be updated;

[0015] Based on the data set that needs to be updated for precision, combined with the actual operating environment of the intelligent sorting terminal, the latest working status of the terminal is generated to adapt to the latest working status.

[0016] Optionally, based on the initial difference report, an incremental synchronization algorithm is used to perform an in-depth analysis of the difference between the cloud storage task template and the current task progress of the intelligent sorting terminal, identify the data items that need to be updated, improve the synchronization efficiency, and generate a list of data that needs to be updated, including:

[0017] Based on the initial difference report, the difference between the cloud storage task template and the current task progress of the intelligent sorting terminal is quantified to generate a difference quantification index;

[0018] Based on the quantitative difference indicators, an incremental synchronization algorithm is used to perform in-depth data analysis, further subdivide specific difference points, formulate corresponding synchronization strategies for different types of data changes, and generate detailed difference analysis results;

[0019] Based on the detailed difference analysis results, a priority ranking model for the data items that need to be updated is constructed to evaluate the impact scope and importance of each difference point, optimize resource allocation, and generate priority labels for the data items that need to be updated;

[0020] Based on the priority labels of the data items that need to be updated, a context-adaptive analysis is performed, and a list of data that needs to be updated is generated through a comprehensive security and compliance review.

[0021] Optionally, based on the list of data to be updated, real-time difference detection technology is used to perform precision processing to avoid repeated and redundant data transmission and generate a precise data set to be updated, including:

[0022] Based on the list of data to be updated, specific data differences are identified through field-level comparison, and a detailed difference list is generated;

[0023] Based on the detailed difference list, use real-time difference detection technology to perform fine-grained analysis, evaluate the latest changes in real time, filter unnecessary update requests, and generate an optimized set of difference points;

[0024] Based on the optimized difference point set, a consistency check is performed in combination with the historical version control information to exclude duplicate updates and processed changes, and a non-duplicate update difference point list is generated;

[0025] Based on the non-duplicate update difference point list, the actual impact scope is evaluated, the workload and environmental parameters are comprehensively considered, the substantial impact is determined, and an accurate data set that needs to be updated is generated.

[0026] Optionally, based on the latest working state of the terminal, a secure transmission algorithm under a zero-trust architecture is used to perform encryption processing, a strict access control and identity authentication mechanism is implemented during data transmission, and a multi-path transmission technology is used to send the data to the corresponding intelligent sorting terminal, and the update processing is completed through a preset secure channel to generate an updated local data state, including:

[0027] Based on the latest working status of the terminal, optimization and pre-screening processing are performed before transmission, importance and urgency are analyzed, and optimized update data packets are generated;

[0028] Based on the optimized update data packet, the secure transmission algorithm under the zero-trust architecture is used for encryption processing, strict access control and identity authentication mechanisms are implemented, the legitimacy of the identity of the intelligent sorting terminal is confirmed, and an encrypted and protected update data packet is generated;

[0029] Based on the encrypted and protected update data packet, a multi-path transmission technology is adopted to send it to the corresponding intelligent sorting terminal through multiple network paths, dynamically select the optimal path, avoid single point failure, and generate a multi-path transmission result;

[0030] Based on the multi-path transmission result, decryption is performed through a preset secure channel, and seamless integration and update processing are performed to generate an updated local data state.

[0031] Optionally, the update data packet based on the optimization is encrypted using a secure transmission algorithm under a zero-trust architecture, a strict access control and identity authentication mechanism is implemented, the legitimacy of the identity of the intelligent sorting terminal is confirmed, and an encrypted update data packet is generated, including:

[0032] Based on the optimized update data package, analyze the security sensitivity of each data item in detail to ensure that key information is fully secure and generate a security assessment report;

[0033] Based on the security assessment report, use the secure transmission algorithm under the zero-trust architecture to determine the security sensitivity level, select the appropriate encryption algorithm and key length for encryption processing, form a highly protected state, and generate a preliminary encrypted update data packet;

[0034] Based on the initially encrypted update data packet, a strict access control and identity authentication mechanism is implemented, each request is fully verified through a multiple identity authentication method to ensure the legitimacy of the identity and generate an identity authentication result;

[0035] Based on the identity authentication result, secure transmission parameters are configured, detailed transmission permissions and security policies are set, and an encrypted and protected update data packet is generated.

[0036] Optionally, based on the updated local data status, feedback confirmation information to the cloud, evaluate and adjust the task allocation and resource configuration of the intelligent sorting terminal, and generate a data synchronization strategy, including:

[0037] Based on the updated local data status, the intelligent sorting terminal is processed for status confirmation, the actual operation status is analyzed, and a terminal status confirmation report is generated;

[0038] Based on the terminal status confirmation report, feedback confirmation information to the cloud, grasp the latest working status of each terminal in real time, and generate feedback confirmation information;

[0039] Based on the feedback confirmation information, evaluate the task allocation and resource allocation of the intelligent sorting terminal, combine historical data with the prediction model, analyze the current task load and resource utilization efficiency, and generate a task allocation evaluation report;

[0040] Based on the task allocation evaluation report, the task priorities are optimized and adjusted to ensure the long-term and efficient operation of the intelligent sorting terminal and generate a data synchronization strategy.

[0041] In a second aspect, an embodiment of the present application provides a system for synchronizing data between an intelligent sorting terminal and a cloud, including:

[0042] The receiving module is used to receive the status update information of the intelligent sorting terminal, perform parsing and processing to understand the specific requirements and current working status of each terminal, and generate a terminal status snapshot;

[0043] An analysis module is used to perform a detailed analysis of the difference between the cloud storage task template and the current task progress based on the terminal status snapshot using an incremental synchronization algorithm, identify the data items that need to be updated, and use real-time difference detection technology to perform precise processing to adapt to the latest working status and generate the latest working status of the terminal;

[0044] A processing module is used to perform encryption processing based on the latest working status of the terminal using a secure transmission algorithm under a zero-trust architecture, implement strict access control and identity authentication mechanisms during data transmission, use multi-path transmission technology, send the data to the corresponding intelligent sorting terminal, complete the update processing through a preset secure channel, and generate an updated local data status;

[0045] The feedback module is used to feedback confirmation information to the cloud based on the updated local data status, evaluate and adjust the task allocation and resource configuration of the intelligent sorting terminal, and generate a data synchronization strategy.

[0046] In a third aspect, an embodiment of the present application provides a computing device, comprising a processing component and a storage component; the storage component stores one or more computer instructions; the one or more computer instructions are used to be called and executed by the processing component to implement a method for synchronizing data between an intelligent sorting terminal and a cloud as described in the first aspect.

[0047] In a fourth aspect, an embodiment of the present application provides a computer storage medium storing a computer program. When the computer program is executed by a computer, a method for synchronizing data between an intelligent sorting terminal and a cloud as described in the first aspect is implemented.

[0048] In the embodiment of the present application, the intelligent sorting terminal status update information is received, parsed and processed to understand the specific needs and current working status of each terminal, and a terminal status snapshot is generated; based on the terminal status snapshot, the incremental synchronization algorithm is used to perform a detailed analysis of the difference between the cloud storage task template and the current task progress, identify the data items that need to be updated, and use real-time difference detection technology to perform precise processing to adapt to the latest working status and generate the latest working status of the terminal; based on the latest working status of the terminal, the secure transmission algorithm under the zero-trust architecture is used to perform encryption processing, and strict access control and identity authentication mechanisms are implemented during data transmission. Multi-path transmission technology is used to send it to the corresponding intelligent sorting terminal, and the update processing is completed through a preset secure channel to generate an updated local data status; based on the updated local data status, the confirmation information is fed back to the cloud, the task allocation and resource allocation of the intelligent sorting terminal are evaluated and adjusted, and a data synchronization strategy is generated. By receiving the intelligent sorting terminal status update information and generating a terminal status snapshot, the system can accurately understand the specific needs and current working status of each terminal. Based on this snapshot, the application of incremental synchronization algorithm and real-time difference detection technology ensures that the difference between the cloud storage task template and the terminal's current task progress can be carefully analyzed, the data items that need to be updated can be identified, and the data can be accurately processed to adapt to the latest working status. Furthermore, the application of secure transmission algorithms, strict access control and authentication mechanisms, and multi-path transmission technology under the zero-trust architecture ensures the security and reliability of data transmission. Finally, by feeding back confirmation information to the cloud, evaluating and adjusting task allocation and resource allocation, the generated data synchronization strategy makes the operation of the entire system more efficient and stable.

[0049] Furthermore, by comparing the cloud storage task template with the current task progress of the intelligent sorting terminal, an initial difference report is generated, and then the incremental synchronization algorithm is used to deeply analyze the differences, identify the data items that need to be updated, and improve the synchronization efficiency. Real-time difference detection technology is used for precise processing to avoid repeated and redundant data transmission and generate accurate data sets that need to be updated. Finally, combined with the actual operating environment of the terminal, the latest working status of the terminal is generated to ensure that the updated content is both accurate and necessary. This method not only improves the accuracy of data synchronization, but also reduces unnecessary data transmission and optimizes system resource utilization.

[0050] Furthermore, encryption processing is performed through a secure transmission algorithm under a zero-trust architecture, and strict access control and authentication mechanisms are implemented to ensure that only legitimate terminals can receive updated data. Multi-path transmission technology and dynamic selection of the optimal path are used to avoid single point failures and ensure the reliability and efficiency of transmission. Finally, seamless integration and update processing are performed through a preset secure channel to generate an updated local data state. This approach not only improves the security and reliability of data transmission, but also maximizes synchronization efficiency and terminal performance by optimizing the content and transmission path of data packets.

[0051] These and other aspects of the present application will become more clearly understood in the description of the following embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0052] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, a brief introduction will be given below to the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0053] Figure 1 A flowchart of a method for synchronizing data between an intelligent sorting terminal and a cloud provided in an embodiment of the present application;

[0054] Figure 2 A schematic diagram of the structure of an intelligent sorting terminal and a cloud data synchronization system provided in an embodiment of the present application;

[0055] Figure 3 A schematic diagram of the structure of a computing device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0056] In order to enable those skilled in the art to better understand the solution of the present application, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application.

[0057] In some of the processes described in the specification and claims of this application and the above-mentioned figures, multiple operations that appear in a specific order are included, but it should be clearly understood that these operations may not be executed in the order in which they appear in this article or executed in parallel. The serial numbers of the operations, such as 101, 102, etc., are only used to distinguish between different operations, and the serial numbers themselves do not represent any execution order. In addition, these processes may include more or fewer operations, and these operations may be executed in sequence or in parallel. It should be noted that the descriptions of "first", "second", etc. in this article are used to distinguish different messages, devices, modules, etc., do not represent the order of precedence, and do not limit the "first" and "second" to be different types.

[0058] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of this application.

[0059] Figure 1 A flowchart of a method for synchronizing data between an intelligent sorting terminal and a cloud is provided for an embodiment of the present application. Figure 1 As shown, the method includes:

[0060] 101. Receive status update information of intelligent sorting terminals, perform analysis and processing to understand the specific requirements and current working status of each terminal, and generate a terminal status snapshot;

[0061] In this step, the status update information of the intelligent sorting terminal includes data such as equipment operating parameters, task progress, and environmental conditions. This information not only reflects the real-time status of the terminal, but may also include error logs, exception reports, and operation records, which are used to fully understand the working conditions of the terminal. It is transmitted to the cloud through the network. After parsing and processing, the system can understand the specific needs and current working status of each terminal.

[0062] A terminal status snapshot is a point-in-time record containing all the above information for subsequent analysis and decision-making. A snapshot is not just a simple data collection, it also includes the preliminary processing results of these data, such as calculating averages, detecting anomalies, etc., in order to more accurately reflect the true status of the terminal.

[0063] In an embodiment of the present application, first, the system receives status update information from the intelligent sorting terminal; second, the information is parsed, key data is extracted and preliminary processing is performed; third, a detailed terminal status snapshot is generated by combining historical data and current context; finally, this snapshot will serve as the basis for subsequent steps to ensure that subsequent analysis and synchronization operations are based on the most accurate data.

[0064] Suppose an intelligent logistics sorting terminal regularly sends its status update information to the cloud, including sensor readings, task completion status, and ambient temperature. First, the cloud receives and parses this information to extract key parameters. Second, it combines historical data to generate a status snapshot of the terminal at a specific point in time. Third, this snapshot not only contains the latest operating parameters, but also records environmental change trends. Finally, it provides a detailed data foundation for subsequent steps.

[0065] 102. Based on the terminal status snapshot, use the incremental synchronization algorithm to carefully analyze the difference between the cloud storage task template and the current task progress, identify the data items that need to be updated, use real-time difference detection technology, perform precise processing to adapt to the latest working status, and generate the latest working status of the terminal;

[0066] In this step, the incremental synchronization algorithm is an optimized data synchronization method that only transmits changed data rather than all data. This method not only reduces unnecessary data transmission, improves synchronization efficiency, but also reduces bandwidth usage and storage requirements.

[0067] Cloud storage task templates are pre-set standard task configurations, including task lists, operation steps, expected completion time, etc. These templates are used as reference benchmarks to compare actual task progress.

[0068] The current task progress is the task status actually executed by the intelligent sorting terminal, including information such as the number of completed tasks, remaining task time, task priority, etc. The difference between the two needs to be identified through careful analysis to determine which data items need to be updated.

[0069] Real-time difference detection technology can detect data changes immediately and perform precise processing to ensure that updates are both accurate and necessary.

[0070] The latest working status of the terminal reflects the optimal status of the terminal after the latest data synchronization, ensuring that it can respond to new task requirements in a timely manner and maintain an efficient workflow.

[0071] In the embodiment of the present application, first, the system conducts a detailed analysis of the difference between the cloud-stored task template and the current task progress based on the terminal status snapshot; secondly, an incremental synchronization algorithm is used to identify the data items that need to be updated; thirdly, real-time difference detection technology is used to perform precise processing to avoid repeated and redundant data transmission; finally, based on the processing results, the latest working status of the terminal is generated to ensure that it adapts to the latest work needs.

[0072] For example, continuing with the above example, the cloud compares the task template stored in the cloud with the current task progress of the terminal based on the generated terminal status snapshot; first, the system finds that the progress of some tasks lags behind expectations; second, through the incremental synchronization algorithm, it identifies the data items that need to be updated, such as new task instructions or revised parameters; third, the real-time difference detection technology confirms the necessity of these updated items and performs precise processing; finally, the latest working status of the terminal is generated to ensure that it can respond to new task requirements in a timely manner.

[0073] 103. Based on the latest working status of the terminal, the secure transmission algorithm under the zero-trust architecture is used to perform encryption processing, strict access control and identity authentication mechanisms are implemented during data transmission, and multi-path transmission technology is used to send the data to the corresponding intelligent sorting terminal, and the update processing is completed through the preset secure channel to generate an updated local data status;

[0074] In this step, zero trust architecture is a modern security model that assumes that internal and external threats are everywhere, so any access request needs to be strictly verified. This architecture emphasizes continuous authentication and authorization to ensure that only legitimate users and devices can access and operate data.

[0075] A secure transmission algorithm refers to an encryption method used to protect data from being stolen or tampered with during transmission. Common algorithms include AES and RSA.

[0076] Access control and authentication mechanisms ensure that only authorized users and devices can access specific resources, preventing unauthorized access.

[0077] Multipath transmission technology allows data to be transmitted through multiple network paths, improving transmission reliability and speed while providing redundancy and avoiding single point failures.

[0078] A preset secure channel refers to a secure communication link established in advance to ensure the security and confidentiality of data transmission.

[0079] The local data status refers to the new status after the terminal receives the updated data, decrypts and integrates it, ensuring that the terminal is always in the latest working status.

[0080] In the embodiment of the present application, first, the system selects a suitable encryption algorithm and key length to perform encryption processing based on the latest working status of the terminal; secondly, during the data transmission process, a strict access control and identity authentication mechanism is implemented to ensure data security; thirdly, multi-path transmission technology is used to dynamically select the optimal path to avoid single point failure; finally, the update processing is completed through a preset secure channel to generate an updated local data status, ensuring that the terminal is always in the latest and secure working state.

[0081] For example, continuing with the above example, the cloud prepares to update the data packet based on the latest working status of the terminal; first, the system uses the AES-256 encryption algorithm to encrypt the data and generate a long key; second, during the transmission process, the access control and authentication mechanism under the zero-trust architecture is used to confirm the legitimacy of the terminal; third, multi-path transmission technology is used to send update data packets through multiple network paths, and the optimal path is selected to ensure transmission speed and reliability; finally, through the preset secure channel, the terminal receives and decrypts the data packet and generates an updated local data status, ensuring that the terminal completes the update safely and efficiently while maintaining high availability and security.

[0082] 104. Based on the updated local data status, feedback confirmation information to the cloud, evaluate and adjust the task allocation and resource configuration of the intelligent sorting terminal, and generate a data synchronization strategy.

[0083] In this step, the feedback confirmation information refers to the confirmation message sent by the terminal to the cloud after receiving the update data, indicating that the update has been successfully completed. This step ensures that the cloud can verify whether the terminal has correctly received and applied the update data.

[0084] Evaluation and adjustment refers to re-evaluating the task allocation and resource configuration of the terminal based on the updated local data status to ensure that it meets the latest work requirements. This process may involve adjusting task priorities, assigning new tasks, optimizing resource utilization, etc.

[0085] The data synchronization strategy is a series of rules and plans generated based on the evaluation results to guide future data synchronization operations and optimize system performance. The content of the strategy may include synchronization frequency, selection of data items, priority sorting, etc., aiming to improve the system's response speed and operating efficiency.

[0086] In an embodiment of the present application, first, the terminal sends feedback confirmation information to the cloud based on the updated local data status; secondly, the cloud evaluates whether the task allocation and resource allocation of the terminal need to be adjusted according to the received confirmation information; thirdly, based on the evaluation results, a new data synchronization strategy is generated; finally, these strategies will guide future data synchronization operations to ensure that the system is always in the best operating state.

[0087] For example, continuing with the above example, after completing the update, the terminal sends feedback confirmation information to the cloud; first, the cloud receives the confirmation information and confirms that the update is successful; second, based on the latest local data status of the terminal, it evaluates whether its task allocation and resource allocation need to be adjusted; third, the cloud generates a new data synchronization strategy to optimize future task allocation and resource utilization; finally, these strategies will guide the terminal to perform tasks more efficiently in future work, ensure the continuous optimization and stable operation of the system, and thus improve the overall operational efficiency and responsiveness.

[0088] In summary, steps 101 to 104 cover the complete process from data item security sensitivity assessment to dynamic adjustment of encryption strength, aiming to provide a comprehensive and flexible secure transmission mechanism to meet the needs of high security, high efficiency and resource optimization in the process of data synchronization between intelligent sorting terminals and the cloud. Through these steps, the system can accurately assess the security risk of each data item, select the most appropriate encryption algorithm and key length, ensure the confidentiality and integrity of key information during transmission, and avoid unnecessary encryption overhead, thereby improving the reliability and response speed of the overall system.

[0089] In order to solve the redundancy and inaccuracy problems that may exist in the data synchronization process, in some embodiments, step 102 is based on the terminal status snapshot, using an incremental synchronization algorithm to perform a detailed analysis of the difference between the cloud storage task template and the current task progress, identify the data items that need to be updated, and use real-time difference detection technology to perform precision processing to adapt to the latest working status and generate the latest working status of the terminal, including: based on the terminal status snapshot, the cloud storage task template and the current task progress of the intelligent sorting terminal are compared and processed to generate an initial difference report; based on the initial difference report, the incremental synchronization algorithm is used to perform an in-depth analysis of the difference between the cloud storage task template and the current task progress of the intelligent sorting terminal, identify the data items that need to be updated, improve the synchronization efficiency, and generate a list of data that needs to be updated; based on the list of data that needs to be updated, real-time difference detection technology is used to perform precision processing to avoid repeated and redundant data transmission, and generate a precise set of data that needs to be updated; based on the precise set of data that needs to be updated, combined with the actual operating environment of the intelligent sorting terminal, to adapt to the latest working status, the latest working status of the terminal is generated.

[0090] In this embodiment, the initial difference report is generated by comparing the cloud storage task template in the terminal status snapshot with the current task progress of the intelligent sorting terminal. It not only records the differences between the two, but also includes a detailed description of the changes, such as the status changes of new tasks, completed tasks and unfinished tasks.

[0091] The list of data that needs to be updated is generated through an incremental synchronization algorithm, which performs an in-depth analysis of the differences in the initial difference report. This list accurately lists the data items that need to be updated, improving synchronization efficiency. It also includes the priority and dependencies of each data item to ensure that the synchronization process proceeds in an orderly manner.

[0092] The precise update data set is to further refine the list of data to be updated through real-time difference detection technology, avoid repeated and redundant data transmission, and ensure that each update item is necessary.

[0093] The actual operating environment of the intelligent sorting terminal refers to the specific physical and technical conditions faced by the terminal at its deployment location, which includes but is not limited to environmental factors such as network connection quality (such as bandwidth, latency), power supply stability, hardware performance (such as CPU, memory, storage capacity), operating temperature and humidity.

[0094] In the embodiment of the present application, first, the system compares the cloud storage task template with the current task progress of the intelligent sorting terminal based on the terminal status snapshot, and generates an initial difference report; secondly, based on the initial difference report, the incremental synchronization algorithm is used to conduct an in-depth analysis of the differences between the cloud storage task template and the current task progress of the intelligent sorting terminal, identify the data items that need to be updated, improve the synchronization efficiency, and generate a list of data that needs to be updated; thirdly, based on the list of data that needs to be updated, real-time difference detection technology is used to perform precise processing to avoid repeated and redundant data transmission, and generate a precise set of data that needs to be updated; finally, combined with the actual operating environment of the intelligent sorting terminal to adapt to the latest working status, the latest working status of the terminal is generated to ensure that it can efficiently respond to new task requirements.

[0095] Here is a specific example:

[0096] Suppose in an intelligent agricultural irrigation management system, first, the system receives a status snapshot sent by the intelligent inspection terminal located in the farmland, finds that the water control parameters of some irrigation areas are different from the standard templates stored in the cloud, and generates an initial difference report; secondly, based on the initial difference report, the system uses an incremental synchronization algorithm to identify the data items that need to be updated, such as new irrigation plans or adjusted water settings, and generates a list of data that needs to be updated; thirdly, through real-time difference detection technology, the necessity of these update items is confirmed, and they are processed precisely to generate a precise data set that needs to be updated, avoiding unnecessary data transmission; finally, the system combines the actual operating environment of the terminal, takes into account the specific soil moisture, weather forecast and power supply of the farmland, and generates the latest working status of the terminal to ensure that it can respond to new task requirements in a timely manner in a complex environment, thereby optimizing overall work efficiency and resource utilization.

[0097] In order to solve the redundancy and inaccuracy problems that may exist in the data synchronization process and further improve the synchronization efficiency and accuracy, in some embodiments, based on the initial difference report described in step 102, an incremental synchronization algorithm is used to conduct an in-depth analysis of the differences between the cloud storage task template and the current task progress of the intelligent sorting terminal, identify the data items that need to be updated, improve the synchronization efficiency, and generate a list of data that needs to be updated, including: based on the initial difference report, the difference between the cloud storage task template and the current task progress of the intelligent sorting terminal is quantified to generate a difference quantification index; based on the difference quantification index, an incremental synchronization algorithm is used to perform in-depth data analysis, further subdivide specific difference points, formulate corresponding synchronization strategies for different types of data changes, and generate detailed difference analysis results; based on the detailed difference analysis results, a priority ranking model for data items that need to be updated is constructed, the impact scope and importance of each difference point are evaluated, resource allocation is optimized, and priority labels for data items that need to be updated are generated; based on the priority labels for data items that need to be updated, context adaptive analysis is performed, and a list of data that needs to be updated is generated through comprehensive security and compliance review.

[0098] In this embodiment, the difference quantification index is a specific numerical value or score generated after the difference in the initial difference report is quantified. These indicators are used to measure the importance, scope of impact and urgency of each difference point, helping the system to more accurately identify which differences need to be processed first. Quantification processing usually includes statistical differences in number, frequency, size and degree of impact on task execution.

[0099] The refined difference analysis results are generated by performing in-depth data analysis on the difference quantitative indicators through the incremental synchronization algorithm. This process further subdivides the specific difference points and formulates corresponding synchronization strategies for different types of data changes.

[0100] The priority ranking model for data items that need to be updated is an evaluation tool used to construct priority labels for data items that need to be updated. It evaluates the impact and importance of each difference point based on the results of detailed difference analysis and optimizes resource allocation.

[0101] The priority label of the data item that needs to be updated is an identifier generated according to the priority sorting model and is used to guide the synchronization operation of the system. Each label reflects the priority and processing order of the corresponding data item, ensuring that high-priority data items can be processed first, thereby improving the overall synchronization efficiency and system response speed.

[0102] Context-adaptive analysis refers to a comprehensive security and compliance review of all data items that need to be updated before generating a list of data that needs to be updated. This process ensures that the updated content complies with the latest security standards and industry specifications, avoiding the introduction of new risks or non-compliance due to data updates.

[0103] In an embodiment of the present application, first, the system quantifies the difference between the cloud storage task template and the current task progress of the intelligent sorting terminal based on the initial difference report, and generates a difference quantification index; secondly, based on the difference quantification index, an incremental synchronization algorithm is used to perform in-depth data analysis, further subdivide the specific difference points, formulate corresponding synchronization strategies for different types of data changes, and generate detailed difference analysis results; thirdly, based on the detailed difference analysis results, a priority sorting model for data items that need to be updated is constructed, the impact scope and importance of each difference point are evaluated, resource allocation is optimized, and priority labels for data items that need to be updated are generated; finally, based on the priority labels of data items that need to be updated, contextual adaptive analysis is performed, and a list of data that needs to be updated is generated through comprehensive security and compliance reviews.

[0104] Here is a specific example:

[0105] Assume that in an intelligent power monitoring system, first, the system receives a status snapshot sent by a power sub-inspection terminal located in a remote area, finds that some power dispatching parameters are different from the standard template stored in the cloud, and generates an initial difference report; secondly, based on the initial difference report, the system quantifies the difference between the task template stored in the cloud and the current task progress of the intelligent sub-inspection terminal, and generates a difference quantification index; thirdly, based on the difference quantification index, the system uses an incremental synchronization algorithm to perform in-depth data analysis, further subdivides specific difference points, such as power load fluctuations, equipment failures, etc., and formulates corresponding synchronization strategies to generate detailed difference analysis results; then, based on the detailed difference analysis results, the system constructs a priority ranking model for data items that need to be updated, evaluates the impact scope and importance of each difference point, optimizes resource allocation, and generates priority labels for data items that need to be updated; finally, based on the priority labels of data items that need to be updated, the system performs contextual adaptability analysis to ensure that the updated content complies with the latest safety standards and industry specifications, generates a list of data that needs to be updated, and ensures that it can respond to new task requirements in a timely manner under resource-constrained conditions, thereby optimizing overall work efficiency and resource utilization.

[0106] In order to solve the duplication and redundancy problems that may exist in the data synchronization process and further improve the synchronization efficiency and accuracy, in some embodiments, based on the list of data to be updated described in step 102, real-time difference detection technology is used to perform precise processing to avoid repeated and redundant data transmission and generate a precise set of data to be updated, including: based on the list of data to be updated, specific data difference points are identified through field-level comparison to generate a detailed difference list; based on the detailed difference list, real-time difference detection technology is used to perform fine-grained analysis, real-time evaluation of the latest changes, filtering unnecessary update requests, and generating an optimized set of difference points; based on the optimized set of difference points, consistency verification is performed in combination with historical version control information to exclude duplicate updates and processed changes, and a list of non-duplicate update difference points is generated; based on the list of non-duplicate update difference points, the actual impact range is evaluated, and the workload and environmental parameters are comprehensively considered to determine the substantial impact and generate a precise set of data to be updated.

[0107] In this embodiment, field-level comparison refers to a detailed field-level comparison of each data item in the data list to be updated to identify specific data differences. This comparison method can accurately find out the changes in each field, such as modification of field values, new or deleted fields, etc.

[0108] The detailed difference list is generated by comparing the data items in the data list to be updated at the field level. It records the differences between specific data items, such as changes in field values, newly added or deleted fields, etc.

[0109] Fine-grained analysis is the process of performing fine-grained analysis on detailed difference schedules through real-time difference detection technology. It not only evaluates the latest changes, but also filters out unnecessary update requests, avoiding redundant data transmission, thereby improving synchronization efficiency.

[0110] The optimized set of differences is the result of fine-grained analysis and includes an impact assessment of each difference to determine its importance and urgency.

[0111] Consistency checking is a consistency check performed in combination with historical version control information. It eliminates duplicate updates and processed changes to ensure that each update item is new and necessary.

[0112] The list of non-duplicate updated difference points is generated after consistency verification, and a unique identifier is marked for each difference point to ensure its traceability throughout the synchronization process.

[0113] Assessing the actual impact scope refers to the process of comprehensively considering workload and environmental parameters to determine the substantial impact. It also includes predicting the actual impact scope and expected effects of the update items in order to better plan resource allocation and task scheduling.

[0114] In an embodiment of the present application, first, the system identifies specific data differences through field-level comparison based on the list of data to be updated, and generates a detailed difference list; secondly, based on the detailed difference list, the system uses real-time difference detection technology to perform fine-grained analysis, evaluates the latest changes in real time, filters unnecessary update requests, and generates an optimized set of difference points; thirdly, based on the optimized set of difference points, a consistency check is performed in combination with historical version control information to exclude duplicate updates and processed changes, and generate a list of non-duplicate update difference points; finally, based on the list of non-duplicate update difference points, the actual impact scope is evaluated, the workload and environmental parameters are comprehensively considered, the substantial impact is judged, and a precise set of data to be updated is generated.

[0115] Here is a specific example:

[0116] Assume that in an intelligent medical monitoring system, first, the system receives a status snapshot sent by an intelligent sorting terminal located in a hospital ward, finds that the configuration parameters of some patient monitoring devices are different from the standard templates stored in the cloud, and generates a list of data that needs to be updated; secondly, based on the list of data that needs to be updated, the system identifies specific data differences through field-level comparison, such as heart rate monitoring frequency, blood oxygen saturation threshold, etc., and generates a detailed difference list; thirdly, based on the detailed difference list, the system uses real-time difference detection technology to perform fine-grained analysis, evaluates the latest changes in real time, filters unnecessary update requests, and generates an optimized set of differences; then, based on the optimized set of differences, the system performs consistency verification in combination with historical version control information, excludes duplicate updates and processed changes, and generates a list of non-duplicate update differences; finally, based on the list of non-duplicate update differences, the system evaluates the actual impact range, comprehensively considers workload and environmental parameters, such as the current number of patients and network conditions, determines the substantial impact, and generates a precise set of data that needs to be updated, ensuring that it can respond to new task requirements in a complex environment in a timely manner, thereby optimizing overall work efficiency and resource utilization.

[0117] In order to solve the security and reliability problems that may exist in the data transmission process and further improve the synchronization efficiency and security, in some embodiments, the step 103 is based on the latest working state of the terminal, uses the secure transmission algorithm under the zero trust architecture, performs encryption processing, implements strict access control and identity authentication mechanism during data transmission, uses multi-path transmission technology, sends it to the corresponding intelligent sorting terminal, completes the update processing through a preset secure channel, and generates an updated local data state, including: based on the latest working state of the terminal, performs optimization and pre-screening processing before transmission, analyzes the importance and urgency, and generates an optimized update data packet; based on the optimized update data packet, uses the secure transmission algorithm under the zero trust architecture to perform encryption processing, implements strict access control and identity authentication mechanism, confirms the legitimacy of the identity of the intelligent sorting terminal, and generates an encrypted and protected update data packet; based on the encrypted and protected update data packet, uses multi-path transmission technology to send it to the corresponding intelligent sorting terminal through multiple network paths, dynamically selects the optimal path, avoids single point failure, and generates a multi-path transmission result; based on the multi-path transmission result, decrypts through a preset secure channel, performs seamless integration and update processing, and generates an updated local data state.

[0118] In this embodiment, the optimization and pre-screening process refers to analyzing the data packet to be updated before transmission, evaluating the importance and urgency of each data item, and removing unnecessary content, thereby generating an optimized update data packet.

[0119] Importance and urgency analysis is to evaluate the priority of data items that need to be updated, and determine which data items need to be updated immediately and which can be delayed or ignored. This process ensures that critical tasks and high-priority data can be processed as soon as possible, improving the response speed and stability of the system.

[0120] The optimized update data package is a data set generated after optimization and pre-screening. It contains all the important information that needs to be updated and is sorted according to its urgency.

[0121] Decryption and seamless integration refers to decrypting the encrypted update data packet at the receiving end and seamlessly integrating it into the existing working environment of the terminal to ensure that the update process does not affect the normal operation of the terminal.

[0122] The updated local data status refers to the new working status generated by the intelligent sorting terminal after receiving and processing the update data packet transmitted from the cloud.

[0123] In the embodiment of the present application, first, the system optimizes and pre-screens the data before transmission based on the latest working status of the terminal, analyzes the importance and urgency, and generates an optimized update data packet; secondly, based on the optimized update data packet, the system uses the secure transmission algorithm under the zero-trust architecture to perform encryption processing, implements strict access control and identity authentication mechanisms, confirms the legitimacy of the identity of the intelligent sorting terminal, and generates an encrypted and protected update data packet; thirdly, based on the encrypted and protected update data packet, multi-path transmission technology is used to send it to the corresponding intelligent sorting terminal through multiple network paths, dynamically selects the optimal path, avoids single point failures, and generates a multi-path transmission result; finally, based on the multi-path transmission result, decryption is performed through a preset secure channel, seamless integration and update processing are performed, and an updated local data status is generated.

[0124] Here is a specific example:

[0125] Suppose in an intelligent traffic management system, first, the system optimizes and pre-screens the data before transmission based on the latest working status of the terminal, analyzes the importance and urgency, and generates an optimized update data packet; secondly, based on the optimized update data packet, it uses the secure transmission algorithm under the zero-trust architecture for encryption processing, implements strict access control and identity authentication mechanisms, confirms the legitimacy of the identity of the intelligent sorting terminal, and generates an encrypted and protected update data packet; thirdly, based on the encrypted and protected update data packet, it uses multi-path transmission technology to send it to the corresponding intelligent sorting terminal through multiple network paths, dynamically selects the optimal path, avoids single point failure, and generates multi-path transmission results; finally, based on the multi-path transmission results, it is decrypted through a preset secure channel, seamlessly integrated and updated, and generates an updated local data status to ensure that it can respond to new task requirements in a complex environment in a timely manner, thereby optimizing overall work efficiency and resource utilization.

[0126] In order to solve the security and sensitive information protection problems that may exist during data transmission and further improve synchronization efficiency and security, in some embodiments, the update data packet based on the optimization described in step 103 is encrypted using a secure transmission algorithm under a zero-trust architecture, a strict access control and identity authentication mechanism is implemented, the legitimacy of the identity of the intelligent sorting terminal is confirmed, and an encrypted and protected update data packet is generated, including: based on the optimized update data packet, a detailed analysis of the security sensitivity of each data item is performed to ensure that key information is fully secure and a security assessment report is generated; based on the security assessment report, a secure transmission algorithm under a zero-trust architecture is used to determine the security sensitivity level, a suitable encryption algorithm and key length are selected for encryption processing, a highly protected state is formed, and a preliminary encrypted update data packet is generated; based on the preliminary encrypted update data packet, a strict access control and identity authentication mechanism is implemented, each request is fully verified through multiple identity authentication methods, the legitimacy of the identity is ensured, and an identity authentication result is generated; based on the identity authentication result, secure transmission parameters are configured, detailed transmission permissions and security policies are set, and an encrypted and protected update data packet is generated.

[0127] In this embodiment, the security assessment report is a document generated after a detailed analysis of each data item in the optimized update data package, which records the security sensitivity of each data item to ensure that key information is fully secure.

[0128] Security sensitivity level refers to the security requirement level of different data items determined based on the security assessment report. The security sensitivity level determines the strength and complexity of subsequent encryption processing, ensuring that data items of different levels can receive corresponding protection.

[0129] The initially encrypted update data packet is generated by selecting a suitable encryption algorithm and key length to encrypt the optimized update data packet. It is in a highly protected state to ensure the confidentiality and integrity of the data during transmission.

[0130] The authentication result is the conclusion after multiple authentications are performed on each request. It confirms the legitimacy of the requester's identity and ensures that only legitimate smart sorting terminals can receive updated data.

[0131] Security transmission parameters refer to a series of configuration options set to ensure secure data transmission, including but not limited to transmission protocols, encryption standards, access rights, etc. They ensure that data will not be tampered with or stolen during transmission.

[0132] Detailed transmission permissions and security policies refer to the specific access rights and security rules set for each terminal. These permissions and policies ensure that only authorized devices can access and operate data under specific conditions, enhancing the security and controllability of the system.

[0133] The encrypted update data package is the final data package generated after multiple authentications and configuration of secure transmission parameters. It not only contains the encrypted update content, but also includes detailed transmission permissions and security policies to ensure the security and reliability of data during transmission.

[0134] In the embodiment of the present application, first, the system analyzes the security sensitivity of each data item in detail based on the optimized update data packet, ensures that key information is fully secure, and generates a security assessment report; secondly, based on the security assessment report, the system uses the secure transmission algorithm under the zero-trust architecture to determine the security sensitivity level, selects the appropriate encryption algorithm and key length for encryption processing, forms a highly protected state, and generates a preliminary encrypted update data packet; thirdly, based on the preliminary encrypted update data packet, implements strict access control and identity authentication mechanisms, and comprehensively verifies each request through multiple identity authentication methods to ensure the legitimacy of the identity and generate an identity authentication result; finally, based on the identity authentication result, configures secure transmission parameters, sets detailed transmission permissions and security policies, and generates an encrypted and protected update data packet.

[0135] Here is a specific example:

[0136] Assume that in an intelligent energy management system, first, based on the optimized update data packet, the system analyzes the security sensitivity of each data item in detail, such as power consumption data, user behavior patterns, etc., to ensure that key information is fully secure and generate a security assessment report; secondly, based on the security assessment report, the system uses the secure transmission algorithm under the zero-trust architecture to determine the security sensitivity level of different data items, selects the appropriate encryption algorithm and key length for encryption processing, forms a highly protected state, and generates a preliminary encrypted update data packet; thirdly, based on the preliminary encrypted update data packet, implements a strict access control and authentication mechanism, and fully verifies each request through multiple authentication methods (such as two-factor authentication and biometrics) to ensure the legitimacy of the identity of the intelligent sorting terminal and generate an authentication result; finally, based on the authentication result, configures secure transmission parameters, sets detailed transmission permissions and security policies, ensures that only authorized intelligent sorting terminals can receive and decrypt update data under specific conditions, and generates encrypted and protected update data packets. The whole process ensures timely response to new task requirements in complex environments, while improving the security and reliability of the system, thereby optimizing overall work efficiency and resource utilization.

[0137] In order to solve the problems of unreasonable task allocation and low resource utilization efficiency that may exist in the process of data synchronization between the intelligent sorting terminal and the cloud, and further improve the response speed and operation efficiency of the system, in some embodiments, based on the updated local data status described in step 104, feedback confirmation information is sent to the cloud, the task allocation and resource configuration of the intelligent sorting terminal are evaluated and adjusted, and a data synchronization strategy is generated, including: based on the updated local data status, the intelligent sorting terminal is processed for status confirmation, the actual operation status is analyzed, and a terminal status confirmation report is generated; based on the terminal status confirmation report, confirmation information is fed back to the cloud, the latest working status of each terminal is grasped in real time, and feedback confirmation information is generated; based on the feedback confirmation information, the task allocation and resource configuration of the intelligent sorting terminal are evaluated, and the current task load and resource utilization efficiency are analyzed in combination with historical data and prediction models to generate a task allocation evaluation report; based on the task allocation evaluation report, the task priority is optimized and adjusted to ensure the long-term and efficient operation of the intelligent sorting terminal and generate a data synchronization strategy.

[0138] In this embodiment, the status confirmation process is a process of performing a detailed analysis on the intelligent sorting terminal to understand its actual operation status.

[0139] The terminal status confirmation report is a document generated by analyzing the status of the intelligent sorting terminal. It describes the current working status of the terminal in detail, including task progress, resource utilization, hardware performance, etc., to help the system evaluate the actual operation of the terminal and provide a basis for subsequent task allocation and resource configuration.

[0140] Feedback confirmation information refers to feeding back key information in the terminal status confirmation report to the cloud, so that the cloud can grasp the latest working status of each terminal in real time. This information is used to generate feedback confirmation information to ensure that the cloud has a clear understanding of the status of all terminals, so as to make more reasonable decisions.

[0141] The task allocation assessment report is generated by combining historical data with predictive models to analyze the current task load and resource utilization efficiency. It not only evaluates the effectiveness of the current task allocation, but also predicts possible changes in the future, providing a scientific basis for optimizing and adjusting task priorities.

[0142] The data synchronization strategy is the result of optimizing and adjusting task priorities based on comprehensive consideration of the task allocation evaluation report to ensure the long-term and efficient operation of the intelligent sorting terminal. It clarifies which tasks need to be prioritized and which resources need to be reallocated to achieve optimal work efficiency and resource utilization.

[0143] In the embodiment of the present application, first, the system performs status confirmation processing on the intelligent sorting terminal based on the updated local data status, analyzes the actual operation status, and generates a terminal status confirmation report; secondly, based on the terminal status confirmation report, the system feeds back confirmation information to the cloud, grasps the latest working status of each terminal in real time, and generates feedback confirmation information; thirdly, based on the feedback confirmation information, the task allocation and resource allocation of the intelligent sorting terminal are evaluated, and the current task load and resource utilization efficiency are analyzed by combining historical data and prediction models to generate a task allocation evaluation report; finally, based on the task allocation evaluation report, the task priority is optimized and adjusted to ensure the long-term and efficient operation of the intelligent sorting terminal and generate a data synchronization strategy.

[0144] Here is a specific example:

[0145] Assume that in an intelligent logistics warehouse management system, first, the system confirms the status of the intelligent sorting terminal (such as the automatic guided vehicle AGV) based on the updated local data status, analyzes the actual operation status, and generates a terminal status confirmation report; secondly, based on the terminal status confirmation report, feedback confirmation information to the cloud, grasp the latest working status of each terminal in real time, and generate feedback confirmation information; thirdly, based on the feedback confirmation information, evaluate the task allocation and resource allocation of the intelligent sorting terminal, combine historical data with the prediction model, analyze the current task load and resource utilization efficiency, and generate a task allocation evaluation report; finally, based on the task allocation evaluation report, optimize and adjust the task priority, ensure the long-term and efficient operation of the intelligent sorting terminal, and generate a data synchronization strategy. For example, during the peak period of the warehouse, increase the working frequency and path optimization of the AGV to reduce the time of cargo handling; and during the non-peak period, reduce the working intensity of the AGV to save energy, ensure the efficient operation of the entire system and the best use of resources.

[0146] This application takes into account that in order to solve the problems of redundant data transmission, resource waste and response delay in the process of data synchronization between the intelligent sorting terminal and the cloud in the prior art, the embodiment of the present invention proposes a deep data analysis method based on difference quantification indicators. This method generates a comprehensive difference weight by performing detailed feature extraction on each data item and combining time sensitivity assessment and anomaly detection to optimize the synchronization strategy. Furthermore, by introducing a comprehensive synchronization priority calculation, the order of data items to be updated is dynamically adjusted to improve synchronization efficiency and resource utilization. Therefore, a new optional scheme is proposed, which includes:

[0147] Based on the quantitative difference indicators, in-depth data analysis is performed to further subdivide specific differences, formulate corresponding synchronization strategies for different types of data changes, and generate detailed difference analysis results, including:

[0148] Based on the difference quantification indicators, detailed feature extraction is performed on each data item, key attributes are identified and weights are assigned, time sensitivity is assessed, potential issues are flagged through anomaly detection, so as to generate a comprehensive difference weight;

[0149] The comprehensive difference weight is calculated by the following formula:

[0150]

[0151] Among them, W i is the comprehensive difference weight of the i-th data item; D ij is the difference between the i-th data item and the cloud template in the j-th feature dimension; j is the index of the feature dimension; N is the number of feature dimensions; w j is the importance weight of the jth feature dimension; α is the time decay factor, which is used to adjust the influence of old data; λ is the time decay rate; T j is the timestamp difference of the jth feature dimension; γ k and δ are adjustment parameters used to control the influence of different factors in the denominator; k is the index of the feature dimension; M is the number of feature dimensions; D ik is the difference between the i-th data item and the cloud template in the k-th feature dimension; T k is the timestamp difference of the kth feature dimension;

[0152] Based on the comprehensive difference weight, the change type of each data item is encoded, and the historical usage frequency and the function impact coefficient are combined for evaluation, the priority is dynamically adjusted, and the synchronization strategy is optimized to generate a comprehensive synchronization priority;

[0153] The comprehensive synchronization priority is calculated using the following formula:

[0154]

[0155] Among them, P i is the comprehensive synchronization priority of the i-th data item; W i is the comprehensive difference weight of the i-th data item; β, γ, δ, η, θ, ζ are adjustment parameters used to control the influence of different factors; C i is the change type code of the i-th data item, where 1 is added, 0.5 is modified, and 0 is deleted; C max is the maximum possible value of the change type, which is 1 in this case; U i is the usage frequency of the i-th data item; U avg is the average usage frequency of all data items; F i is the functional impact coefficient of the ith data item; V i Score the value of the i-th data item; V maxis the highest value score among all data items; μ is the functional impact factor; S i Synchronizes the progress of data items in the current state; S prev is the data item progress at the last synchronization; ∈ is a small constant to prevent division by zero;

[0156] Based on the comprehensive synchronization priority, the current CPU memory and storage resource occupancy is evaluated through resource utilization prediction technology, and a dynamic adaptive adjustment mechanism is introduced to predict and fine-tune the order of data items that need to be updated, thereby generating detailed difference analysis results.

[0157] This method aims to reduce unnecessary data transmission, improve synchronization efficiency, and ensure that high-priority tasks are processed in a timely manner through precise data analysis and priority evaluation. At the same time, by introducing resource utilization prediction technology and dynamic adaptive adjustment mechanism, the system can still run efficiently under resource constraints.

[0158] In the comprehensive difference weight, the square of the feature dimension difference is multiplied by the importance weight term w j ·|D ij | 2 :This sub-item is used to measure the impact of the difference in each feature dimension on the overall difference; the greater the difference and the more important the dimension, the greater its contribution to the total weight; the time decay factor affects the old data item This sub-item takes into account the time factor, making newer data changes have higher weights, while older changes gradually lose influence; the adjustment parameter controls the influence of different factors in the denominator γ k ·|D ik |: This item is used to balance the relative influence of different feature dimensions and ensure the reasonable distribution of weights of each dimension; it controls the influence item of timestamp difference δ·log(1+T k ): This sub-item uses logarithmic transformation to reduce the impact of long time spans, avoiding excessive interference of too large time differences on the comprehensive weight;

[0159] Among them, w j Importance weight derived from historical data analysis; D ij and D ik is the difference value of the data item extracted from the terminal state snapshot; α and λ are time decay parameters set empirically; T j and T k is the time difference extracted from the timestamp of the data item; γ k and δ are pre-set tuning parameters;

[0160] Exponential decay terms of difference weights and functional impact in comprehensive synchronization priorities This sub-item reflects the nonlinear combination of the comprehensive difference weight and the functional impact coefficient, emphasizing the priority of tasks with high difference weight and high functional impact; the sine function mapping item of the change type This sub-item converts the change type code into a value between 0 and 1, with new tasks given the highest priority and deleted tasks given the lowest priority; the logarithmic conversion item of the frequency of use This sub-item enhances the priority of frequently used data items through logarithmic transformation, while avoiding the impact of extreme values; the proportional scaling item of the value score This item scales the value score proportionally to ensure that high-value data items have higher priority; the change rate of the synchronization progress This sub-item evaluates the stability and urgency of data items by the rate of change of synchronization progress;

[0161] Among them, W i Calculated from the previous step; F i It is the functional impact coefficient obtained based on historical data analysis; C i and C max Set according to the change type code; U i Obtained by counting usage frequency; U avg is the average usage frequency of all data items; V i and V max It is determined based on a value scoring system; S i and S prev is obtained by recording the synchronization progress; β, γ, δ, η, θ, ζ, μ, ∈ are pre-set adjustment parameters;

[0162] Assume that in an intelligent agricultural irrigation monitoring system, for the i-th data item (such as soil moisture monitoring data), the number of feature dimensions N = M = 5, and the importance weight of the feature dimension w j =[0.2, 0.2, 0.3, 0.1, 0.2], time decay factor α = 0.8, time decay rate λ = 0.1, adjustment parameter γ k =[0.1, 0.2, 0.3, 0.2, 0.2], δ = 0.5, feature dimension difference value D ij =[0.1, 0.2, 0.3, 0.4, 0.5], timestamp difference T j = [1, 2, 3, 4, 5];

[0163]

[0164] Assume that the adjustment parameters β = 0.6, γ = 0.5, δ = 0.3, η = 0.2, θ = 0.4, ζ = 0.5, the functional impact factor μ = 0.7, and the change type code C i =1 (newly added), maximum possible value C max=1, frequency of use U i = 20 times / hour, average frequency of use U avg =15 times / hour, functional impact coefficient F i =0.8, value score V i =90, the highest value score V max =100, the data item synchronization progress S in the current state i =0.6, data item progress S at the last synchronization prev =0.4; the first step of substituting data

[0165] Assuming that the threshold is set to 0.9, since the calculated result 0.92 is greater than the set threshold, it indicates that the soil moisture monitoring data has a higher synchronization priority and needs to be synchronized immediately; this is because the higher comprehensive synchronization priority reflects the importance and urgency of the data under current environmental conditions, while ensuring the efficient operation of the system and the best use of resources; through the above steps, the timeliness and accuracy of the synchronization of soil moisture monitoring data are ensured, the management efficiency and scientificity of the agricultural irrigation system are improved, and the accuracy and response speed of the entire intelligent agricultural monitoring system are enhanced.

[0166] This application takes into account that in order to solve the problems of inaccurate security risk assessment, overly rigid encryption strategy and unreasonable resource utilization in the process of synchronizing data between intelligent sorting terminals and the cloud in the prior art, the embodiment of the present invention proposes a secure transmission algorithm based on a security assessment report. This method extracts and evaluates the key attributes of each data item, and identifies abnormal activities in combination with behavioral pattern analysis to determine potential security risks and calculate security sensitivity; further, by introducing encryption strength calculation, the encryption algorithm selection and key length are dynamically adjusted to ensure that highly sensitive data items use stronger encryption measures, while avoiding performance degradation caused by excessive encryption; therefore, a new optional solution is proposed, which includes:

[0167] Based on the security assessment report, the security transmission algorithm under the zero-trust architecture is used to determine the security sensitivity level, select the appropriate encryption algorithm and key length for encryption processing, form a highly protected state, and generate a preliminary encrypted update data packet, including:

[0168] Based on the security assessment report, extract and evaluate key attributes of each data item to determine potential security risks;

[0169] Identify abnormal activities through behavioral pattern analysis, combine historical operation records with current workloads, and evaluate the actual usage scenario of each data item to generate security sensitivity;

[0170] The security sensitivity is calculated using the following formula:

[0171]

[0172] Among them, S i is the security sensitivity of the i-th data item; D ij is the difference value of the i-th data item on the j-th feature dimension; j is the index of the feature dimension; N is the number of feature dimensions; w j is the importance weight of the jth feature dimension; α' is the time factor; T j is the timestamp difference of the jth feature dimension; β k is the behavior influence coefficient; λ' is the behavior decay rate; B ik is the dynamic behavior score of the i-th data item; j is the index of the behavior score dimension; M is the number of behavior score dimensions;

[0173] Based on the security sensitivity, fine classification processing is performed, and the encryption algorithm selection and key length are dynamically adjusted to ensure that highly sensitive data items use stronger encryption measures, introduce resource utilization, avoid performance degradation caused by over-encryption, and generate encryption strength;

[0174] The encryption strength is calculated using the following formula:

[0175]

[0176] Among them, E i is the encryption strength of the i-th data item; S i is the calculated security sensitivity of the i-th data item; γ, δ, η, θ, φ, ζ, ψ are adjustment parameters; C i Encode the change type of the i-th data item; C max is the maximum possible value of the change type; U i is the usage frequency of the i-th data item; U avg is the average usage frequency of all data items; V i Score the value of the i-th data item; V max Give the highest value score among all data items; A i A is the access frequency of the data item currently evaluated; avg is the average access frequency of all data items; A prev is the access frequency of the data item last evaluated; ∈ is a small constant to prevent division by zero; I l is the lth identity authentication score; Q l The quality score of the lth access request; Q m is the quality score of the mth access request; l and m are the indices of authentication and access requests; L is the number of authentication and access requests; ν is the tuning parameter; P mScore the priority of the mth access request;

[0177] Based on the encryption strength, it is encapsulated into a preset security protocol, necessary metadata is attached, a unique identifier and a timestamp are embedded to ensure the integrity and non-repudiation of the transmission process, and a preliminary encrypted update data packet is generated.

[0178] This method aims to reduce unnecessary encryption overhead, improve the security and efficiency of data transmission, and ensure that highly sensitive data is fully protected through accurate security assessment and dynamic encryption strategy. At the same time, by introducing resource utilization prediction technology and dynamic adaptive adjustment mechanism, the system can still run efficiently under resource constraints.

[0179] In security sensitivity, the feature dimension difference is multiplied by the importance weight term w j ReLU(D ij ): This sub-item is used to measure the impact of the difference in each feature dimension on the overall security risk; the larger the difference and the more important the dimension, the greater its contribution to the total sensitivity; the time factor affects the old data item α'·log(1+T j ): This sub-item takes into account the time factor, making newer data changes have higher weights, while older changes gradually lose influence; the behavior influence coefficient is multiplied by the exponential decay term This sub-item reflects the importance of the behavioral scoring dimension and emphasizes the impact of current behavioral patterns on future security risks;

[0180] Among them, w j Importance weight derived from historical data analysis; D ij is the difference value of the data item extracted from the terminal state snapshot; α' is the time factor set based on experience; T j is the time difference extracted from the timestamp of the data item; β k and λ' are the pre-set behavior influence coefficient and behavior decay rate; B ik It is a dynamic behavior score derived from the analysis of user behavior patterns;

[0181] In encryption strength, security sensitivity is multiplied by the adjustment parameter γ·S i :This item maps security sensitivity directly to encryption strength, ensuring that highly sensitive data items are more strongly encrypted; Change type sine function mapping item This sub-item converts the change type code into a value between 0 and 1, with new tasks given the highest priority and deleted tasks given the lowest priority; use the logarithmic conversion item of frequency This sub-item enhances the encryption strength of high-frequency data items through logarithmic transformation, while avoiding the influence of extreme values; the value score hyperbolic tangent scaling term θ· This item scales the value score proportionally to ensure that high-value data items have higher encryption strength; the square root of the access frequency adjustment item This sub-item evaluates the access frequency of data items through square root conversion to prevent over-encryption from affecting performance; the access frequency change rate item This sub-item evaluates the stability and urgency of data items by the rate of change of access frequency; the weighted average of the authentication score This sub-item takes into account the authentication score and the quality score of the access request to ensure that the operations of legitimate users are properly encrypted;

[0182] Among them, S i Calculated by the safety sensitivity formula; C i and C max Set according to the change type code; U i Obtained by counting usage frequency; U avg is the average usage frequency of all data items; V i and V max It is determined based on a value scoring system; A i and A prev is obtained by recording the access frequency; ∈ is a small constant to prevent division by zero; I l , Q l and Q m It is based on the quality score of authentication and access request; m is the priority score of the mth access request; γ, δ, η, θ, φ, ζ, ψ, v are pre-set adjustment parameters;

[0183] Assume that an intelligent traffic management system is built in a city. To improve the reliability and scientificity of the traffic management system, first, for the i-th data item (such as traffic flow monitoring data), let the number of feature dimensions N = M = 5 and the importance weight of the feature dimension w j =[0.2, 0.2, 0.3, 0.1, 0.2], time factor α'=0.8, behavior influence coefficient β k =[0.1, 0.2, 0.3, 0.2, 0.2], behavior decay rate λ' = 0.1, feature dimension difference value D ij =[0.1, 0.2, 0.3, 0.4, 0.5], timestamp difference T j =[1, 2, 3, 4, 5], dynamic behavior score B ik = [0.9, 0.8, 0.7, 0.6, 0.5];

[0184]

[0185] Assume that the adjustment parameters γ = 0.6, δ = 0.3, η = 0.2, θ = 0.4, φ = 0.5, ζ = 0.5, ψ = 0.7, ν = 0.1, and change the type code C i =1 (newly added), maximum possible value C max =1, frequency of use U i = 20 times / hour, average frequency of use U avg =15 times / hour, functional impact coefficient F i =0.8, value score V i =90, the highest value score V max =100, the access frequency of the data item currently evaluated is A i = 0.6, the access frequency of the data item in the last evaluation A prev =0.4, identity verification score I l =[0.9, 0.8, 0.7], the quality score Q of the access request l =[0.8, 0.7, 0.6], Q m =[0.8, 0.7, 0.6]; priority score P of access request m = [0.7, 0.6, 0.5];

[0186]

[0187] Assuming that the threshold is set to 0.9, since the calculated result 0.93 is greater than the set threshold, it shows that the traffic flow monitoring data has a high encryption strength, which can ensure that the data is not tampered with or leaked during transmission and storage; this is because the higher encryption strength index reflects that the encryption algorithm can effectively protect the security of the data under the current network conditions without affecting the transmission efficiency and decryption speed; through the above steps, the security and privacy protection of traffic flow monitoring data transmission are ensured, the reliability and scientificity of the traffic management system are improved, and the accuracy and response speed of the entire smart city traffic management system are enhanced.

[0188] Figure 2 A schematic diagram of the structure of a smart sorting terminal and a cloud data synchronization system is provided for an embodiment of the present application. Figure 2 As shown, the device comprises:

[0189] The receiving module 21 is used to receive the intelligent sorting terminal status update information, perform parsing and processing to understand the specific requirements and current working status of each terminal, and generate a terminal status snapshot;

[0190] The analysis module 22 is used to perform a detailed analysis of the difference between the cloud storage task template and the current task progress based on the terminal status snapshot using an incremental synchronization algorithm, identify the data items that need to be updated, and use real-time difference detection technology to perform precise processing to adapt to the latest working status and generate the latest working status of the terminal;

[0191] The processing module 23 is used to perform encryption processing based on the latest working status of the terminal, use the secure transmission algorithm under the zero-trust architecture, implement strict access control and identity authentication mechanism during data transmission, use multi-path transmission technology, send it to the corresponding intelligent sorting terminal, complete the update processing through the preset secure channel, and generate an updated local data status;

[0192] The feedback module 24 is used to feed back confirmation information to the cloud based on the updated local data status, evaluate and adjust the task allocation and resource configuration of the intelligent sorting terminal, and generate a data synchronization strategy.

[0193] Figure 2 The intelligent sorting terminal and cloud data synchronization system can perform Figure 1 The implementation principle and technical effect of the intelligent sorting terminal and cloud data synchronization method described in the embodiment are not repeated here. The specific way in which each module and unit performs operations in the intelligent sorting terminal and cloud data synchronization system in the above embodiment has been described in detail in the embodiment of the method, and will not be elaborated here.

[0194] In one possible design, Figure 2 The intelligent sorting terminal and cloud data synchronization system of the embodiment shown can be implemented as a computing device, such as Figure 3 As shown, the computing device may include a storage component 31 and a processing component 32;

[0195] The storage component 31 stores one or more computer instructions, wherein the one or more computer instructions are called and executed by the processing component 32 .

[0196] The processing component 32 is used to: receive the intelligent sorting terminal status update information, perform parsing processing to understand the specific needs and current working status of each terminal, and generate a terminal status snapshot; based on the terminal status snapshot, use the incremental synchronization algorithm to perform a detailed analysis of the difference between the cloud storage task template and the current task progress, identify the data items that need to be updated, use real-time difference detection technology, perform precise processing to adapt to the latest working status, and generate the latest working status of the terminal; based on the latest working status of the terminal, use the secure transmission algorithm under the zero-trust architecture to perform encryption processing, implement strict access control and identity authentication mechanisms during data transmission, use multi-path transmission technology, send it to the corresponding intelligent sorting terminal, complete the update processing through a preset secure channel, and generate an updated local data status; based on the updated local data status, feedback confirmation information to the cloud, evaluate and adjust the task allocation and resource allocation of the intelligent sorting terminal, and generate a data synchronization strategy.

[0197] The processing component 32 may include one or more processors to execute computer instructions to complete all or part of the steps in the above method. Of course, the processing component may also be implemented by one or more application-specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field programmable gate arrays (FPGAs), controllers, microcontrollers, microprocessors or other electronic components to perform the above method.

[0198] The storage component 31 is configured to store various types of data to support operations at the terminal. The storage component can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk or optical disk.

[0199] Of course, the computing device may also include other components, such as input / output interfaces, display components, communication components, etc.

[0200] The input / output interface provides an interface between the processing component and the peripheral interface module, which may be an output device, an input device, etc.

[0201] The communication component is configured to facilitate, among other things, wired or wireless communications between the computing device and other devices.

[0202] Among them, the computing device can be a physical device or an elastic computing host provided by a cloud computing platform, etc. In this case, the computing device can refer to a cloud server, and the above-mentioned processing components, storage components, etc. can be basic server resources rented or purchased from the cloud computing platform.

[0203] The present application also provides a computer storage medium storing a computer program, wherein the computer program can achieve the above-mentioned Figure 1 A method for synchronizing data between an intelligent sorting terminal and a cloud in the illustrated embodiment.

[0204] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0205] The device embodiments described above are merely illustrative, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. Ordinary technicians in this field can understand and implement it without paying creative labor.

[0206] Through the description of the above implementation methods, those skilled in the art can clearly understand that each implementation method can be implemented by means of software plus a necessary general hardware platform, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solution is essentially or the part that contributes to the prior art can be embodied in the form of a software product, and the computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a disk, an optical disk, etc., including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or some parts of the embodiments.

[0207] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit it. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. A method for synchronizing data between an intelligent sorting terminal and a cloud, characterized in that: include: Receive status update information of intelligent sorting terminals, parse and process it to understand the specific requirements and current working status of each terminal, and generate a terminal status snapshot; Based on the terminal status snapshot, the incremental synchronization algorithm is used to carefully analyze the difference between the cloud storage task template and the current task progress, identify the data items that need to be updated, and use real-time difference detection technology to perform precise processing to adapt to the latest working status and generate the latest working status of the terminal; Based on the latest working status of the terminal, the secure transmission algorithm under the zero-trust architecture is used for encryption processing, strict access control and identity authentication mechanisms are implemented during data transmission, and multi-path transmission technology is used to send the data to the corresponding intelligent sorting terminal. The update processing is completed through the preset secure channel to generate an updated local data status; Based on the updated local data status, the confirmation information is fed back to the cloud, the task allocation and resource configuration of the intelligent sorting terminal are evaluated and adjusted, and a data synchronization strategy is generated.

2. The method according to claim 1, characterized in that Based on the terminal status snapshot, the incremental synchronization algorithm is used to carefully analyze the difference between the cloud storage task template and the current task progress, identify the data items that need to be updated, and use real-time difference detection technology to perform precise processing to adapt to the latest working status and generate the latest working status of the terminal, including: Based on the terminal status snapshot, the cloud storage task template is compared with the current task progress of the intelligent sorting terminal to generate an initial difference report; Based on the initial difference report, an incremental synchronization algorithm is used to conduct an in-depth analysis of the differences between the cloud storage task template and the current task progress of the intelligent sorting terminal, identify the data items that need to be updated, improve synchronization efficiency, and generate a list of data that needs to be updated; Based on the list of data to be updated, real-time difference detection technology is used to perform precise processing to avoid repeated and redundant data transmission and generate a precise data set to be updated; Based on the data set that needs to be updated for precision, combined with the actual operating environment of the intelligent sorting terminal, the latest working status of the terminal is generated to adapt to the latest working status.

3. The method according to claim 2, characterized in that Based on the initial difference report, the incremental synchronization algorithm is used to conduct an in-depth analysis of the differences between the cloud storage task template and the current task progress of the intelligent sorting terminal, identify the data items that need to be updated, improve the synchronization efficiency, and generate a list of data that needs to be updated, including: Based on the initial difference report, the difference between the cloud storage task template and the current task progress of the intelligent sorting terminal is quantified to generate a difference quantification index; Based on the quantitative difference indicators, an incremental synchronization algorithm is used to perform in-depth data analysis, further subdivide specific difference points, formulate corresponding synchronization strategies for different types of data changes, and generate detailed difference analysis results; Based on the detailed difference analysis results, a priority ranking model for the data items that need to be updated is constructed to evaluate the impact scope and importance of each difference point, optimize resource allocation, and generate priority labels for the data items that need to be updated; Based on the priority labels of the data items that need to be updated, a context-adaptive analysis is performed, and a list of data that needs to be updated is generated through a comprehensive security and compliance review.

4. The method according to claim 2, characterized in that: Based on the list of data to be updated, real-time difference detection technology is used to perform precise processing to avoid repeated and redundant data transmission and generate a precise data set to be updated, including: Based on the list of data to be updated, specific data differences are identified through field-level comparison, and a detailed difference list is generated; Based on the detailed difference list, use real-time difference detection technology to perform fine-grained analysis, evaluate the latest changes in real time, filter unnecessary update requests, and generate an optimized set of difference points; Based on the optimized difference point set, a consistency check is performed in combination with the historical version control information to exclude duplicate updates and processed changes, and a non-duplicate update difference point list is generated; Based on the non-duplicate update difference point list, the actual impact scope is evaluated, the workload and environmental parameters are comprehensively considered, the substantial impact is determined, and an accurate data set that needs to be updated is generated.

5. The method according to claim 1, characterized in that Based on the latest working status of the terminal, the secure transmission algorithm under the zero-trust architecture is used to perform encryption processing, implement strict access control and identity authentication mechanisms during data transmission, use multi-path transmission technology, send to the corresponding intelligent sorting terminal, complete the update processing through the preset secure channel, and generate an updated local data status, including: Based on the latest working status of the terminal, optimization and pre-screening processing are performed before transmission, importance and urgency are analyzed, and optimized update data packets are generated; Based on the optimized update data packet, the secure transmission algorithm under the zero-trust architecture is used for encryption processing, strict access control and identity authentication mechanisms are implemented, the legitimacy of the identity of the intelligent sorting terminal is confirmed, and an encrypted and protected update data packet is generated; Based on the encrypted and protected update data packet, a multi-path transmission technology is adopted to send it to the corresponding intelligent sorting terminal through multiple network paths, dynamically select the optimal path, avoid single point failure, and generate a multi-path transmission result; Based on the multi-path transmission result, decryption is performed through a preset secure channel, and seamless integration and update processing are performed to generate an updated local data state.

6. The method according to claim 5, characterized in that The update data packet based on the optimization is encrypted using a secure transmission algorithm under a zero-trust architecture, a strict access control and identity authentication mechanism is implemented, the legitimacy of the identity of the intelligent sorting terminal is confirmed, and an encrypted and protected update data packet is generated, including: Based on the optimized update data package, analyze the security sensitivity of each data item in detail to ensure that key information is fully secure and generate a security assessment report; Based on the security assessment report, use the secure transmission algorithm under the zero-trust architecture to determine the security sensitivity level, select the appropriate encryption algorithm and key length for encryption processing, form a highly protected state, and generate a preliminary encrypted update data packet; Based on the initially encrypted update data packet, a strict access control and identity authentication mechanism is implemented, each request is fully verified through a multiple identity authentication method to ensure the legitimacy of the identity and generate an identity authentication result; Based on the identity authentication result, secure transmission parameters are configured, detailed transmission permissions and security policies are set, and an encrypted and protected update data packet is generated.

7. The method according to claim 1, characterized in that Based on the updated local data status, feedback confirmation information to the cloud, evaluate and adjust the task allocation and resource configuration of the intelligent sorting terminal, and generate a data synchronization strategy, including: Based on the updated local data status, the intelligent sorting terminal is processed for status confirmation, the actual operation status is analyzed, and a terminal status confirmation report is generated; Based on the terminal status confirmation report, feedback confirmation information to the cloud, grasp the latest working status of each terminal in real time, and generate feedback confirmation information; Based on the feedback confirmation information, evaluate the task allocation and resource allocation of the intelligent sorting terminal, combine historical data with the prediction model, analyze the current task load and resource utilization efficiency, and generate a task allocation evaluation report; Based on the task allocation evaluation report, the task priorities are optimized and adjusted to ensure the long-term and efficient operation of the intelligent sorting terminal and generate a data synchronization strategy.

8. An intelligent sorting terminal and cloud data synchronization system, characterized in that: include: The receiving module is used to receive the status update information of the intelligent sorting terminal, perform parsing and processing to understand the specific requirements and current working status of each terminal, and generate a terminal status snapshot; An analysis module is used to perform a detailed analysis of the difference between the cloud storage task template and the current task progress based on the terminal status snapshot using an incremental synchronization algorithm, identify the data items that need to be updated, and use real-time difference detection technology to perform precise processing to adapt to the latest working status and generate the latest working status of the terminal; A processing module is used to perform encryption processing based on the latest working status of the terminal using a secure transmission algorithm under a zero-trust architecture, implement strict access control and identity authentication mechanisms during data transmission, use multi-path transmission technology, send the data to the corresponding intelligent sorting terminal, complete the update processing through a preset secure channel, and generate an updated local data status; The feedback module is used to feedback confirmation information to the cloud based on the updated local data status, evaluate and adjust the task allocation and resource configuration of the intelligent sorting terminal, and generate a data synchronization strategy.

9. A computing device, characterized in that It comprises a processing component and a storage component; the storage component stores one or more computer instructions; the one or more computer instructions are used to be called and executed by the processing component to implement a method for synchronizing data between an intelligent sorting terminal and a cloud as described in any one of claims 1 to 7.

10. A computer storage medium, characterized in that: A computer program is stored, and when the computer program is executed by a computer, a method for synchronizing data between an intelligent sorting terminal and a cloud as described in any one of claims 1 to 7 is implemented.

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