Industrial Data Encoding and Transmission Optimization Method, System, Device and Medium Based on Industrial Internet of Things

Abstract

The present invention discloses an industrial data encoding and transmission optimization method, system, device and medium based on the industrial Internet of Things, which relates to the technical field of data transmission processing, and includes: obtaining industrial data to be processed, source characteristics and source length; when the data volume exceeds the source length, forming data packets to be sent, and obtaining the first sequential encoding; planning a basic transmission path and obtaining the second sequential encoding; associating the first sequential encoding and the second sequential encoding with the data packets to be sent to form a data set to be transmitted, and transmitting the data set to be transmitted according to the basic transmission path corresponding to the second sequential encoding; receiving the data set to be transmitted, obtaining a transmission path optimization strategy according to the first sequential encoding of the received data set to be transmitted, and carrying out data transmission of subsequent data packets to be sent according to the transmission path optimization strategy. An industrial data encoding and transmission optimization system based on the industrial Internet of Things is also provided. The present invention has the advantages of good transmission effect, high transmission efficiency and stability and reliability.

Description

Technical Field

[0001] The present invention relates to the technical field of data transmission processing, and particularly relates to an industrial data encoding and transmission optimization method, system, device and medium based on the industrial Internet of Things. Background Art

[0002] With the rapid development of the Industrial Internet of Things (IIoT for short), the acquisition, encoding and efficient transmission of industrial data have become the basis for realizing key applications such as intelligent manufacturing, remote monitoring, and predictive maintenance. In an industrial environment, various sensors, devices and control systems continuously generate a large amount of data, which includes the real-time state of the production process, the health status of equipment, energy consumption information, etc., and is of great significance for improving the operation efficiency of enterprises, optimizing the production process, and reducing the downtime due to faults. However, the particularity and complexity of industrial data have brought huge challenges to data encoding and transmission.

[0003] Existing data encoding and transmission methods often adopt a fixed data packet size and a single transmission path, ignoring the dynamic characteristics of different industrial data sources and the complexity of the network environment; for example, some data may require more frequent sampling and transmission due to the rapid changes in the production process, while some data may be relatively stable and do not require such high-frequency updates; in this way, adopting a unified data packet length and transmission strategy will not only lead to low data transmission efficiency, but also may increase unnecessary network burden due to encoding redundancy, and even cause data loss or transmission delay in some cases, affecting subsequent data analysis and decision-making. In addition, there are numerous transmission nodes in the industrial Internet of Things, and the network environment is complex and changeable. A fixed transmission path is difficult to adapt to the dynamic changes of the network conditions, such as node failures, network congestion, etc., which further exacerbates the instability and unreliability of data transmission. Summary of the Invention

[0004] Aiming at the defects in the prior art, the present invention provides an industrial data encoding and transmission optimization method, system, device and medium based on the industrial Internet of Things.

[0005] An industrial data encoding and transmission optimization method based on the industrial Internet of Things, comprising: obtaining industrial data to be processed based on the industrial Internet of Things, obtaining the source characteristics corresponding to the industrial data to be processed, and obtaining the source length corresponding to the industrial data to be processed according to the source characteristics corresponding to the industrial data to be processed; when the data volume of the industrial data to be processed exceeds the source length, packing the industrial data to be processed to form a data packet to be sent, and obtaining a continuously increasing first sequential code corresponding to the current data packet to be sent based on the first coding model; planning a plurality of basic transmission paths including different transmission nodes, and obtaining a second sequential code corresponding to each basic transmission path based on the position data of the plurality of transmission nodes in each basic transmission path; associating the first sequential code and the second sequential code with the data packet to be sent to form a data set to be transmitted, and transmitting the data set to be transmitted according to the basic transmission path corresponding to the second sequential code; receiving the data set to be transmitted, obtaining a transmission path optimization strategy according to the first sequential code of the received data set to be transmitted, and carrying out data transmission of subsequent data packets to be sent according to the transmission path optimization strategy.

[0006] Optionally, obtaining a transmission path optimization strategy according to the first sequential code of the received data set to be transmitted includes: if the first sequential code of the currently received data set to be transmitted is not continuous with the first sequential code of the previously received data set to be transmitted, and the first sequential code of the currently received data set to be transmitted is greater than the first sequential code of the previously received data set to be transmitted, then obtaining the interval difference between the first sequential code of the currently received data set to be transmitted and the first sequential code of the previously received data set to be transmitted; obtaining the maximum interval difference among a plurality of interval differences within a preset time period, and obtaining the second sequential code of the currently received data set to be transmitted corresponding to the maximum interval difference, and using the basic transmission path corresponding to the second sequential code as the optimized transmission path.

[0007] Optionally, carrying out data transmission of subsequent data packets to be sent according to the transmission path optimization strategy includes: associating the first sequential code with the subsequent data packets to be sent to form a new data set to be transmitted, and transmitting the new data set to be transmitted according to the optimized transmission path.

[0008] Optionally, obtaining a continuously increasing first sequential code corresponding to the current data packet to be sent based on the first coding model includes: setting a continuous increment value and an initial coding value corresponding to the first formation of the data packet to be sent; obtaining the number of times of forming the data packet to be sent between the first formation of the data packet to be sent and the current data packet to be sent; obtaining a continuously increasing first sequential code corresponding to the current data packet to be sent based on the first coding model, the number of times of forming the data packet to be sent, the initial coding value, and the continuous increment value.

[0009] Optionally, the first coding model in the first sequential coding that continuously increases and corresponds to the current data packet to be sent is obtained based on the first coding model, the number of times the data packet to be sent is formed, the initial coding value, and the continuous increment value, which is expressed as: ; where is the i-th first sequential coding, is the number of times the data packet to be sent is formed, is the continuous increment value, is the initial coding value.

[0010] Optionally, obtaining the second sequential coding corresponding to each basic transmission path based on the position data of multiple transmission nodes in each basic transmission path includes: obtaining all the transmission nodes in the j-th basic transmission path, and obtaining the corresponding unique identifier according to the position data of the obtained transmission nodes; obtaining the second sequential coding corresponding to the j-th basic transmission path based on the order of the transmission nodes in the j-th basic transmission path and the unique identifier corresponding to each transmission node.

[0011] Optionally, the system includes a management platform, a sensing network platform, and an object platform that are sequentially communicatively connected. The management platform includes: a comprehensive acquisition module, configured to acquire the industrial data to be processed based on the industrial Internet of Things, acquire the source characteristics corresponding to the industrial data to be processed, and obtain the source length corresponding to the industrial data to be processed according to the source characteristics corresponding to the industrial data to be processed; a judgment and sequential coding module, configured to, when the data volume of the industrial data to be processed exceeds the source length, pack the industrial data to be processed to form a data packet to be sent, and obtain the first sequential coding that continuously increases and corresponds to the current data packet to be sent based on the first coding model; a position coding module, configured to plan multiple basic transmission paths including different transmission nodes, and obtain the second sequential coding corresponding to each basic transmission path based on the position data of multiple transmission nodes in each basic transmission path; a transmission module, configured to associate the first sequential coding and the second sequential coding with the data packet to be sent to form a data set to be transmitted, and transmit the data set to be transmitted according to the basic transmission path corresponding to the second sequential coding; an optimization module, configured to receive the data set to be transmitted, obtain a transmission path optimization strategy according to the first sequential coding of the received data set to be transmitted, and perform subsequent data transmission of the data packet to be sent according to the transmission path optimization strategy.

[0012] Optionally, the optimization module is further configured to: if the first sequence code of the currently received data set to be transmitted is not continuous with the first sequence code of the previously received data set to be transmitted, and the first sequence code of the currently received data set to be transmitted is greater than the first sequence code of the previously received data set to be transmitted, then obtain the interval difference between the first sequence code of the currently received data set to be transmitted and the first sequence code of the previously received data set to be transmitted; obtain the maximum interval difference among multiple interval differences within a preset time period, and obtain the second sequence code of the currently received data set to be transmitted corresponding to the maximum interval difference, and use the basic transmission path corresponding to the second sequence code as the optimized transmission path; associate the first sequence code with the subsequent data packets to be sent to form a new data set to be transmitted, and transmit the new data set to be transmitted according to the optimized transmission path.

[0013] An electronic device is further provided, including: a memory on which a computer program is stored; a processor configured to execute the computer program in the memory to implement the above-mentioned industrial data encoding and transmission optimization method based on the industrial Internet of Things.

[0014] A non-transitory computer-readable storage medium is further provided, on which a computer program is stored, and when the program is executed by a processor, the above-mentioned industrial data encoding and transmission optimization method based on the industrial Internet of Things is implemented.

[0015] The beneficial effects of the present invention are as follows:

[0016] In the whole industrial data encoding and transmission optimization method based on the industrial Internet of Things, firstly, by deeply analyzing the source characteristics of different industrial data sources, the dynamic adjustment of the data packet size is realized, significantly improving the data transmission efficiency and avoiding the coding redundancy and increased network burden caused by the fixed data packet size; at the same time, the first sequence code is introduced to ensure the uniqueness, orderliness and traceability of the data packets during the transmission process, providing strong support for data recombination, error detection and recovery; in addition, by planning multiple basic transmission paths and assigning a unique second sequence code to each path, not only the data shunting and load balancing are realized, but also the system is endowed with high flexibility and adaptability, enabling it to dynamically adjust the data transmission path according to the real-time changes of the network environment and data characteristics, effectively coping with uncertain factors such as node failures and network congestion, and ensuring the stability, reliability and timeliness of data transmission; therefore, this optimization method that comprehensively considers data characteristics, network environment and transmission node uncertainty greatly improves the efficiency and quality of data transmission in the industrial Internet of Things, laying a solid foundation for subsequent data analysis, decision-making and production optimization. Description of the Drawings

[0017] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the following will briefly introduce the drawings required for the description of the specific embodiments or the prior art. In all the drawings, similar elements or parts are generally identified by similar reference numerals. In the drawings, the elements or parts are not necessarily drawn to actual scale.

[0018] Figure 1 Schematic diagram of the steps of the industrial data encoding and transmission optimization method based on the industrial Internet of Things of the present invention;

[0019] Figure 2 Partial schematic diagram of the steps of S5 in the industrial data encoding and transmission optimization method based on the industrial Internet of Things of the present invention;

[0020] Figure 3 Partial schematic diagram of the steps of S2 in the industrial data encoding and transmission optimization method based on the industrial Internet of Things of the present invention;

[0021] Figure 4 Partial schematic diagram of the steps of S3 in the industrial data encoding and transmission optimization method based on the industrial Internet of Things of the present invention;

[0022] Figure 5 Schematic diagram of the composition of the industrial data encoding and transmission optimization system based on the industrial Internet of Things of the present invention;

[0023] Figure 6 Schematic diagram of the composition of the optimized industrial Internet of Things related to the present invention;

[0024] Figure 7 Block diagram of an electronic device shown in an embodiment of the present invention.

[0025] Reference numerals:

[0026] 700 - Electronic device, 701 - Processor, 702 - Memory, 703 - Multimedia component, 704 - I / O interface, 705 - Communication component. Specific embodiments

[0027] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the drawings in the embodiments of the present invention. Obviously, the described embodiments are some, but not all, of the embodiments of the present invention. Usually, the components of the embodiments of the present invention described and shown in the drawings here can be arranged and designed in various different configurations.

[0028] Accordingly, the following detailed description of the embodiments of the present invention provided in the accompanying drawings is not intended to limit the scope of the claimed invention, but merely represents selected embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the scope of protection of the present invention.

[0029] It should be noted that like reference numerals and letters denote like items in the following drawings. Therefore, once an item is defined in one drawing, it does not need to be further defined and explained in subsequent drawings. In addition, the terms "first", "second", etc. are only used for descriptive distinction and cannot be construed as indicating or implying relative importance.

[0030] As Figure 1 shown, an industrial data encoding and transmission optimization method based on the industrial Internet of Things is provided, including:

[0031] S1. Obtain the industrial data to be processed based on the industrial Internet of Things, obtain the source characteristics corresponding to the industrial data to be processed, and obtain the source length corresponding to the industrial data to be processed according to the source characteristics corresponding to the industrial data to be processed;

[0032] S2. When the data volume of the industrial data to be processed exceeds the source length, pack the industrial data to be processed to form a data packet to be sent, and obtain a first sequential code that continuously increases and corresponds to the current data packet to be sent based on the first encoding model;

[0033] S3. Plan multiple basic transmission paths including different transmission nodes, and obtain a second sequential code corresponding to each basic transmission path based on the location data of the multiple transmission nodes in each basic transmission path;

[0034] S4. Associate the first sequential code and the second sequential code with the data packet to be sent to form a data set to be transmitted, and transmit the data set to be transmitted according to the basic transmission path corresponding to the second sequential code;

[0035] S5. Receive the data set to be transmitted, obtain a transmission path optimization strategy according to the first sequential code of the received data set to be transmitted, and carry out the data transmission of subsequent data packets to be sent according to the transmission path optimization strategy.

[0036] In this embodiment, it should be noted that in S1, first, various sensors or data acquisition devices of the industrial Internet of Things are used to obtain industrial data to be processed. These data may include, but are not limited to, various types of physical quantities or status information such as temperature, pressure, humidity, vibration, etc. When obtaining these data, in-depth analysis is carried out on each data type to extract its unique source characteristics. The source characteristics may cover multiple dimensions such as the source of the data, size, fluctuation range, change frequency, importance level, and correlation with other data. For example, for temperature data, it may be found that it changes frequently and is crucial for production safety, so a higher priority and a shorter data update cycle are assigned to it; while for humidity data, if its change is relatively stable and has little impact on production, a longer sampling interval and a lower data priority may be set. Based on these source characteristics, the source length corresponding to each data type, that is, the size of the data packet, is further determined; in this way, the source length can also be dynamic and adjusted according to the real-time characteristics and requirements of the data to ensure the efficient transmission and processing of the data.

[0037] Taking a smart factory as an example, this factory has deployed a variety of sensors to monitor all aspects of the production line. Among them, the sensor used to monitor the temperature inside the reactor finds that the temperature data fluctuates greatly in a short period of time, and this fluctuation is directly related to the quality and production safety of the product. Therefore, in step S1, the source characteristics of this temperature data are analyzed, its characteristics of high-frequency change and criticality are identified, and a relatively short source length, such as 10k, is set accordingly. In contrast, the data of the sensor used to monitor the humidity in the warehouse is relatively stable and changes little, and a longer source length, such as 200k, may be set. In this way, the size of the source length can be flexibly adjusted according to the characteristics and requirements of different data, laying a solid foundation for subsequent coding and transmission optimization.

[0038] In S2, the formation of data packets and coding is further refined. When the data volume of the industrial data to be processed under the same source characteristics accumulates to exceed the source length determined in step S1, the data sending mechanism is triggered. First, it is packaged to form a data packet to be sent, and at the same time, according to the characteristics and importance of the data, and a preset first coding model, a unique and continuously increasing first sequential coding is assigned to the data packet to be sent. This coding is the unique identifier of the data packet identity. It can not only ensure the traceability of the data packet during the transmission process, but also provides an important basis for subsequent data recombination, error detection and recovery. The construction of the first coding model takes into account the timing of the data and possible concurrent transmission requirements to ensure that each data packet can be accurately identified and located in the complex and changeable industrial Internet of Things environment.

[0039] Taking the temperature control of an intelligent factory as an example, assume that in S1, 10k has been determined as the source length according to the source characteristics of the temperature data. That is, whenever the temperature data volume accumulates to 10k, a data packet to be sent is formed. In step S2, when the temperature sensor continuously monitors and accumulates 10k of temperature data, the data packet sending mechanism is triggered. At this time, according to the first coding model and the timing of the current data packet to be sent, a unique first sequential code is generated for this data packet, such as "1442", indicating that this is the 1442nd data packet to be sent. Subsequently, when the temperature data accumulates to 10k again, the next consecutive first sequential code is generated, such as "1443". In this way, each data packet to be sent is given a unique and ordered identifier. Even if data packets are lost or out of order during transmission, the receiving end can quickly locate, report errors, and request retransmission of the lost data packets according to the first sequential code, thereby ensuring the integrity and continuity of the data.

[0040] In S3, it involves the planning and coding of the transmission path. In this step, first, according to the actual situation of the industrial Internet of Things, multiple basic transmission paths containing different transmission nodes are planned. The selection of these paths takes into account multiple factors such as the geographical location of the nodes, network bandwidth, transmission delay, node stability, and possible failure risks, and is generally obtained based on existing historical information. Subsequently, the location data of the transmission nodes in each basic transmission path is collected and analyzed, which includes the physical location of the nodes or their logical location in the network. Based on this information, a unique second sequential code is generated for each basic transmission path. This code is not only an identifier of the path identity but also an important basis for subsequent transmission path optimization decisions.

[0041] Continuing with the temperature control example in the smart factory, in S3, three basic transmission paths may be planned: Path 1 goes from the data convergence point through data relay points 1, 3, and 6 and sends to the central control; Path 2 goes from the data convergence point through data relay points 2, 3, and 4 and sends to the central control; Path 3 goes from the data convergence point through data relay points 2 and 5 and sends to the central control. Next, a unique second-order code will be generated for each path. For example, Path 1 is encoded as "T136", Path 2 as "T234", and Path 3 as "T25". These codes can not only clearly identify and manage different transmission paths. More importantly, during the data transmission process, if it is detected that a certain path (such as Path 2) has a decreased transmission efficiency due to network congestion or node failure, it can quickly locate the problem path according to the second-order code "T234", and based on the transmission path optimization strategy, dynamically adjust the data transmission path. For example, the subsequent temperature data is transmitted through Path 1 or Path 3 to ensure that the temperature data can reach the central control in a timely and accurate manner, providing strong support for the temperature control of the factory.

[0042] In S4, it is necessary to associate the previously generated first-order code and second-order code with the data packet to be sent to form a complete data set to be transmitted. This association process ensures that each data packet has a unique identity identifier and transmission path identifier, and also provides an important basis for subsequent data transmission, reception, and possible error detection and recovery. Specifically, the data set to be transmitted will be sent to the specified transmission path according to the basic transmission path corresponding to the second-order code. By distributing different data packets to the corresponding transmission paths according to the second-order code generated in S3, data shunting and load balancing are achieved. In addition, the continuity of the first-order code also ensures the orderliness of the data packets during the transmission process. Even if data packets are lost or out of order, the receiving end can quickly locate and request retransmission according to the first-order code, thus ensuring the integrity and accuracy of the data. This association and transmission mechanism fully considers the dynamic characteristics of data, the complexity of the network environment, and the uncertainty of transmission nodes in the industrial Internet of Things, providing strong guarantee for the efficient and stable transmission of data.

[0043] In S5, not only the reception of data needs to be processed, but also the transmission strategy needs to be dynamically adjusted according to the received data situation. In S5, first, the data set to be transmitted generated according to S4 is received. This data set contains the first-order encoding and the second-order encoding of the data packets. During the reception process, the first-order encoding of each data packet will be carefully recorded, which serves as the basis for the orderly reception and subsequent processing of the data packets. At the same time, the received data packets will be deeply analyzed, especially focusing on the continuity of the first-order encoding, to detect whether there are data packet losses or transmission delays. If discontinuity or delay is found, the error handling mechanism will be immediately activated, including but not limited to requesting the retransmission of the lost data packets, adjusting the data transmission rate, or re-planning the transmission path. This deep analysis and dynamic adjustment mechanism require a high degree of intelligence and adaptability, capable of responding in real time to changes in the network environment and data characteristics, ensuring the integrity and accuracy of data transmission. In addition, the S5 step also implies the continuous optimization of the transmission path. It will dynamically select the optimal transmission path according to historical transmission data and the current network conditions to further improve the efficiency and stability of data transmission.

[0044] For example, if it is detected that the transmission delay on path 2 ("T234") increases, it may automatically switch the subsequent temperature data to be transmitted on path 1 ("T136") or path 3 ("T25") to ensure the timely arrival of the data. Thus, it has comprehensive network monitoring capabilities, fast data analysis capabilities, and flexible transmission path adjustment capabilities, ensuring that data can be efficiently and stably transmitted to the destination in the complex and changeable industrial Internet of Things environment.

[0045] In summary, in the entire industrial data encoding and transmission optimization method based on the industrial Internet of Things, first, by deeply analyzing the source characteristics of different industrial data sources, the dynamic adjustment of the data packet size is realized, significantly improving the efficiency of data transmission and avoiding the coding redundancy and increased network burden caused by a fixed data packet size. At the same time, the first-order encoding is introduced to ensure the uniqueness, orderliness, and traceability of the data packets during transmission, providing strong support for data recombination, error detection, and recovery. In addition, by planning multiple basic transmission paths and assigning a unique second-order encoding to each path, not only the data shunting and load balancing are realized, but also the system is given a high degree of flexibility and adaptability, enabling it to dynamically adjust the data transmission path according to the real-time changes in the network environment and data characteristics, effectively coping with uncertain factors such as node failures and network congestion, and ensuring the stability, reliability, and timeliness of data transmission. Therefore, this optimization method that comprehensively considers data characteristics, network environment, and the uncertainty of transmission nodes greatly improves the efficiency and quality of data transmission in the industrial Internet of Things, laying a solid foundation for subsequent data analysis, decision-making, and production optimization.

[0046] Figure 2 It is a partial step schematic diagram of S5 in the industrial data encoding and transmission optimization method based on the industrial Internet of Things of the present invention. In one embodiment, obtaining the transmission path optimization strategy according to the first-order encoding of the received data set to be transmitted in S5 includes:

[0047] S51. If the first-order encoding of the currently received data set to be transmitted is not continuous with the first-order encoding of the previously received data set to be transmitted, and the first-order encoding of the currently received data set to be transmitted is greater than the first-order encoding of the previously received data set to be transmitted, then obtain the interval difference between the first-order encoding of the currently received data set to be transmitted and the first-order encoding of the previously received data set to be transmitted;

[0048] S52. Obtain the maximum interval difference among multiple interval differences within a preset time period, and obtain the second-order encoding of the currently received data set to be transmitted corresponding to the maximum interval difference. Use the basic transmission path corresponding to the second-order encoding as the optimized transmission path.

[0049] In this embodiment, it should be noted that in S51, the discontinuity and delay problems in the data transmission process are detected. In this step, a detailed comparison and analysis will be carried out on the first-order encoding of each received data set to be transmitted. If it is found that the first-order encoding of the currently received data set to be transmitted is not continuous with the first-order encoding of the previously received data set to be transmitted, and the current encoding value is greater than the previous encoding, this means that there are packet losses, transmission delays, and transmission in advance in the data transmission process. At this time, the interval difference between these two encodings will be immediately calculated. This difference directly reflects the severity of data loss and delay or the degree of transmission in advance. That is to say, the interval difference reflects the time advantage obtained when the currently received data set to be transmitted is transmitted through the basic transmission path. In this way, step S51 can not only detect abnormalities in data transmission in a timely manner, but also provide accurate data support for subsequent transmission path optimization, ensuring the integrity and timeliness of data transmission.

[0050] In S52, first set a preset time period, and only need to ensure that there are multiple interval differences within the preset time period. Then, determine the largest interval difference among these calculated multiple time interval differences. This maximum interval difference is not only a quantitative index, but more intuitively shows the maximum amount of time that the corresponding currently received data set to be transmitted can save when transmitting data through the basic transmission path, reflecting the significant time advantage of this basic transmission path; Therefore, based on this consideration, select the basic transmission path that shows the greatest potential for time saving as the optimized transmission path for the subsequent transmission process.

[0051] In one embodiment, the data transmission of subsequent data packets to be sent according to the transmission path optimization strategy in S5 includes:

[0052] S53. Associate the first-order encoding with subsequent data packets to be sent to form a new data set to be transmitted, and transmit the new data set to be transmitted according to the optimized transmission path.

[0053] In this embodiment, it should be noted that in S53, it involves precisely associating the first-order encoding generated in the previous steps with the subsequent industrial data packets to be sent to form a new data set to be transmitted, and performing the actual data transmission according to the transmission path (i.e., the optimized transmission path) selected through in-depth analysis and optimization before. In this process, the system needs to ensure that each data packet to be sent is assigned a unique and continuous first-order encoding, which not only carries the identity information of the data packet but also ensures the orderliness and traceability of the data packet during transmission and reception. Subsequently, the system will identify the basic transmission path with the greatest time advantage according to the second-order encoding corresponding to the maximum interval difference determined in step S52 as the current optimized transmission path. Immediately afterwards, the system will transmit the newly generated data set to be transmitted efficiently according to the network configuration and transmission protocol of this optimized path. In this way, it can process the encoding, path selection, data transmission, and possible error detection and recovery of data packets in real time, ensuring that data can be transmitted to the destination in the fastest and most stable manner in the complex and changeable industrial Internet of Things environment, providing solid data support for subsequent data analysis, decision-making, and production optimization.

[0054] It should also be noted that after transmitting the new data set to be transmitted according to the optimized transmission path for a certain period of time, it can return to the steps of S3, re-plan multiple basic transmission paths, and then cycle through the subsequent steps to select a new optimized transmission path to achieve dynamic optimization; by continuously cycling through this optimization process, the system can continuously adapt to changes in the network environment and data characteristics, and achieve continuous improvement in data transmission efficiency and quality.

[0055] Figure 3 This is a schematic diagram of some steps of S2 in the industrial data encoding and transmission optimization method based on the industrial Internet of Things of the present invention. In one embodiment, the steps of obtaining the continuously increasing first-order encoding corresponding to the current data packet to be sent based on the first encoding model in S2 include:

[0056] S21. Set a continuous increment value and an initial encoding value corresponding to the first formation of the data packet to be sent.

[0057] S22. Obtain the number of times the data packet to be sent is formed between the first formation of the data packet to be sent and the current data packet to be sent.

[0058] S23. Obtain a continuously increasing first sequential code corresponding to the current data packet to be sent based on the first coding model, the number of times the data packet to be sent is formed, the initial coding value, and the continuous increment value.

[0059] In this embodiment, it should be noted that in S21, two key parameters need to be set first: the continuous increment value and the initial coding value. The continuous increment value is a fixed value that determines the increase in the coding of each subsequent data packet relative to the coding of the previous data packet. It ensures the continuity and uniqueness of the coding. Even in high-concurrency scenarios of data transmission, each data packet can be accurately distinguished. The selection of this increment value needs to comprehensively consider the generation frequency of data packets, the bandwidth of the transmission network, and the processing capacity of the receiving end to ensure that the generation of coding does not become a bottleneck in data transmission. The initial coding value is the coding assigned to the first data packet to be sent. It serves as the starting point of the entire coding sequence. Although its selection is relatively flexible, it is usually set to a value that is easy to identify and process, such as "1" or "1000", etc., for subsequent coding calculations and data management. The setting of these two parameters lays a solid foundation for the first coding model, enabling each data packet to be assigned a unique and continuously increasing coding, thus meeting various requirements in the data transmission process.

[0060] In S22, it is necessary to track the data acquisition situation in real time. When the accumulated data reaches the preset source length, the formation of data packets is triggered. By recording the time when each data packet to be sent is formed during this process, the system can accurately calculate the number of times the data packet to be sent is formed. This number not only reflects the data generation speed but also provides a necessary basis for subsequent coding generation.

[0061] In S23, based on the previously set continuous increment value, initial coding value, and the calculated number of times the data packet to be sent is formed, the first sequential code corresponding to the current data packet to be sent can be generated according to the first coding model. That is, add the initial coding value to (the number of times the data packet to be sent is formed - 1) multiplied by the continuous increment value. This coding not only ensures that each data packet has a unique identity but also, through its continuity, provides strong support for error detection, data packet recombination, and transmission path optimization during data transmission. More importantly, the generation of this coding is completely automated and can be dynamically adjusted according to the real-time generation situation of data, thus meeting the requirements of high efficiency and flexibility in data transmission in the industrial Internet of Things.

[0062] In one embodiment, the first coding model in obtaining the continuously increasing first sequential code corresponding to the current data packet to be sent based on the first coding model, the number of times the data packet to be sent is formed, the initial coding value, and the continuous increment value in S23 is expressed as:

[0063] ; wherein,

[0064] is the i-th first-order code, is the number of times of forming data packets to be sent, is the continuous increment value, is the initial code value.

[0065] In this embodiment, it should be noted that through this item, it is ensured that each first-order code increases continuously based on the sending order of the data packets to be sent. This helps the receiving party to correctly reorganize and sort the received data packets according to the code order. As an initial offset, it can ensure that the coding sequence starts from a specific value instead of always starting from 0 or 1, which helps to meet specific coding requirements or avoid coding conflicts in specific application scenarios. and The values of can be flexibly set as needed. For example, if a larger interval between codes is desired, the value of can be increased; if the code is desired to start from a specific numerical value, the corresponding value can be set. This setting method enables the coding scheme to easily adapt to different data packet sending scenarios and requirements. At the same time, the calculation speed of the entire linear function is fast and will not bring additional computational burden to the data packet coding process.

[0066] Figure 4 This is a partial step schematic diagram of S3 in the industrial data coding and transmission optimization method based on industrial Internet of Things of the present invention. In one embodiment, obtaining the second-order code corresponding to each basic transmission path based on the position data of multiple transmission nodes in each basic transmission path in S3 includes:

[0067] S31. Obtain all the transmission nodes in the j-th basic transmission path, and obtain the corresponding unique identifier according to the position data of the obtained transmission nodes;

[0068] S32. Obtain the second-order code corresponding to the j-th basic transmission path based on the order of the transmission nodes in the j-th basic transmission path and the unique identifier corresponding to each transmission node.

[0069] In this embodiment, it should be noted that in S31, first, for the j-th basic transmission path, the position data of all transmission nodes on this path are obtained. These position data can include the actual coordinates of the nodes in the physical space (such as longitude and latitude, altitude, etc.), or can cover the logical position information of the nodes in the network architecture (such as IP address, network level, etc.). Subsequently, a unique and stable identifier is assigned to each transmission node, and this identifier is the sole representative of the node's identity and can help quickly locate and identify the node in the network. In this way, step S31 ensures that each transmission node is accurately incorporated into the coding system of the basic transmission path, laying a solid foundation for the generation of the second-order coding subsequently.

[0070] In S32, an ordered coding process is performed on the transmission nodes on the j-th basic transmission path. This process first requires strict sorting of them according to the actual order of the transmission nodes in the path. The basis for sorting may include multiple factors such as the physical location, logical location, transmission priority, and network latency of the nodes to ensure that the coding can truly reflect the relative position and transmission characteristics of the nodes in the path. Subsequently, a unique and highly recognizable second-order coding is generated for the j-th basic transmission path by using the unique identifier assigned to each node in step S31. This coding is not only an accurate identification of the path identity but also an important basis for subsequent data transmission, path optimization, and fault handling.

[0071] Specifically, first, the set of unique identifiers to be encoded is determined. The set of unique identifiers is composed of the unique identifiers corresponding to all transmission nodes in the j-th basic transmission path. Then, multiple unique identifiers in the set of unique identifiers are sequentially concatenated together according to the transmission order of the j-th basic transmission path, and a specific delimiter (such as an underscore) can be used to distinguish different identifiers. Finally, the concatenated string is used as the second-order coding. This coding contains the information of all unique identifiers and is organized according to the order of the transmission path.

[0072] An industrial data coding and transmission optimization system based on the industrial Internet of Things is also provided. The system includes a management platform, a sensing network platform, and an object platform that are communicatively connected in sequence. The management platform includes:

[0073] A comprehensive acquisition module, which is used to acquire industrial data to be processed based on the industrial Internet of Things, acquire the source characteristics corresponding to the industrial data to be processed, and acquire the source length corresponding to the industrial data to be processed according to the source characteristics corresponding to the industrial data to be processed;

[0074] A judgment and sequential coding module, which is used to pack the industrial data to be processed and form a data packet to be sent when the data volume of the industrial data to be processed exceeds the source length, and obtain a continuously increasing first sequential coding corresponding to the current data packet to be sent based on the first coding model;

[0075] A position coding module, which is used to plan multiple basic transmission paths including different transmission nodes, and obtain a second sequential coding corresponding to each basic transmission path based on the position data of multiple transmission nodes in each basic transmission path and the second coding model;

[0076] A transmission module, which is used to associate the first sequential coding and the second sequential coding with the data packet to be sent and form a data set to be transmitted, and transmit the data set to be transmitted according to the basic transmission path corresponding to the second sequential coding;

[0077] An optimization module, which is used to receive the data set to be transmitted, obtain a transmission path optimization strategy according to the first sequential coding of the received data set to be transmitted, and carry out the data transmission of the subsequent data packets to be sent according to the transmission path optimization strategy.

[0078] In one embodiment, the optimization module is further used to: if the first sequential coding of the currently received data set to be transmitted is not continuous with the first sequential coding of the previously received data set to be transmitted, and the first sequential coding of the currently received data set to be transmitted is greater than the first sequential coding of the previously received data set to be transmitted, then obtain the interval difference between the first sequential coding of the currently received data set to be transmitted and the first sequential coding of the previously received data set to be transmitted; obtain the maximum interval difference among multiple interval differences within a preset time period, and obtain the second sequential coding of the currently received data set to be transmitted corresponding to the maximum interval difference, and use the basic transmission path corresponding to the second sequential coding as the optimized transmission path; associate the first sequential coding with the subsequent data packets to be sent and form a new data set to be transmitted, and transmit the new data set to be transmitted according to the optimized transmission path.

[0079] In one embodiment, the position coding module is further used to: obtain all the transmission nodes in the jth basic transmission path, and obtain the corresponding unique identifier according to the position data of the obtained transmission nodes; obtain the second sequential coding corresponding to the jth basic transmission path based on the second coding model, the order of the transmission nodes in the jth basic transmission path, and the unique identifier corresponding to each transmission node.

[0080] In this embodiment, it should be noted that regarding the above industrial data coding and transmission optimization system based on the industrial Internet of Things, the specific manner of performing operations has been described in detail in the embodiments of the industrial data coding and transmission optimization method based on the industrial Internet of Things, and will not be elaborated here.

[0081] It should also be noted that the entire industrial data coding and transmission optimization system based on the industrial Internet of Things can be applied to the optimized industrial Internet of Things. Figure 5 This is a schematic diagram of the composition of the industrial data coding and transmission optimization system based on the industrial Internet of Things of the present invention. Figure 6 This is a schematic diagram of the composition of the optimized industrial Internet of Things related to the present invention. As Figure 5 and Figure 6 shown, the optimized industrial Internet of Things includes a user platform, a service platform, a management platform, a sensing network platform, and an object platform that establish communications in sequence;

[0082] The user platform is configured to provide the function of front-end services to users; users obtain the required perception service information through the user platform, process the perception service information, and convert it into user perception information; users analyze the user perception information and make corresponding decisions in combination with their own wishes, and convert the user perception information into user control information through the corresponding information system and send it to the service platform, thereby showing the corresponding service demand wishes of users.

[0083] The physical entities of the user platform include various user terminals, such as mobile phones, computers, dedicated terminals, etc., and realize the services at the user end through the combination with the user information system software.

[0084] The service platform is configured as an API server or other servers used to establish communications between the management platform and the user platform to achieve corresponding functions; the physical entities of the service platform include various servers.

[0085] The management platform is configured to perform at least one of device operation status monitoring management, data monitoring management, device parameter management, and life cycle management; the management platform is the operation and coordination platform of the Internet of Things and may include various management sub-platforms, and different management sub-platforms perform different management services; the physical entities of the management platform include various servers.

[0086] The sensing network platform is configured to perform at least one of network management, instruction management, device status management, data protocol management, data parsing, data classification, data transmission monitoring, and data transmission security management. The sensing network platform provides functions such as communication transmission, parsing, identification, and classification of data, avoiding the direct aggregation of data from various object platforms in the management platform, resulting in redundant data in the management platform and low data processing efficiency; the physical entities of the object platform include various gateways, edge computing devices, etc.

[0087] The object platform is configured to perform specific production control, detection, metering, and other production work; the physical entities of the production object include various production devices, sensors, etc.

[0088] Figure 7The block diagram of an electronic device for an industrial data encoding and transmission optimization method based on the industrial Internet of Things shown according to an exemplary embodiment. As Figure 7 shown, the electronic device 700 may include: a processor 701, a memory 702. The electronic device 700 may further include one or more of a multimedia component 703, an I / O interface 704 (input / output interface), and a communication component 705.

[0089] Among them, the processor 701 is used to control the overall operation of the electronic device 700 to complete all or part of the steps in the above-mentioned industrial data encoding and transmission optimization method based on the industrial Internet of Things. The memory 702 is used to store various types of data to support the operation of the electronic device 700. These data may include, for example, instructions for any application or method operating on the electronic device 700, as well as application-related data, such as contact data, received and sent messages, pictures, audio, video, and so on. The memory 702 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. The multimedia component 703 may include a screen and an audio component. Among them, the screen can be, for example, a touch screen, and the audio component is used to output and / or input audio signals. For example, the audio component may include a microphone, and the microphone is used to receive external audio signals. The received audio signals can be further stored in the memory 702 or sent through the communication component 705. The audio component also includes at least one speaker for outputting audio signals. The I / O interface 704 provides an interface between the processor 701 and other interface modules. The above-mentioned other interface modules can be a keyboard, a mouse, buttons, etc. These buttons can be virtual buttons or physical buttons. The communication component 705 is used for wired or wireless communication between the electronic device 700 and other devices. Wireless communication, such as Wi-Fi, Bluetooth, near field communication (NFC), 2G, 3G, 4G, NB-IOT, eMTC or other 5G, etc., or a combination of one or more of them is not limited here. Therefore, the corresponding communication component 705 may include: a Wi-Fi module, a Bluetooth module, an NFC module, and so on.

[0090] In an exemplary embodiment, the electronic device 700 can 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, and is used to execute the above-mentioned industrial data encoding and transmission optimization method based on the industrial Internet of Things.

[0091] In another exemplary embodiment, a computer-readable storage medium including program instructions is also provided. When the program instructions are executed by a processor, the steps of the above-mentioned industrial data encoding and transmission optimization method based on the industrial Internet of Things are implemented. For example, the computer-readable storage medium can be the above-mentioned memory 702 including program instructions, and the above program instructions can be executed by the processor 701 of the electronic device 700 to complete the above-mentioned industrial data encoding and transmission optimization method based on the industrial Internet of Things.

[0092] In another exemplary embodiment, a computer program product is also provided. The computer program product includes a computer program that can be executed by a programmable device, and the computer program has a code part for executing the above-mentioned industrial data encoding and transmission optimization method based on the industrial Internet of Things when executed by the programmable device.

[0093] The preferred embodiments of the present disclosure have been described in detail above with reference to the accompanying drawings. However, the present disclosure is not limited to the specific details in the above embodiments. Within the scope of the technical concept of the present disclosure, various simple modifications can be made to the technical solutions of the present disclosure, and these simple modifications all fall within the protection scope of the present disclosure.

[0094] In addition, it should be noted that, in the above specific embodiments, the various specific technical features described can be combined in any suitable manner without conflict. To avoid unnecessary repetition, the present disclosure does not separately describe various possible combination methods.

[0095] Furthermore, any combination can be made between various different embodiments of the present disclosure as long as it does not violate the idea of the present disclosure, and it should also be regarded as the content disclosed by the present disclosure.

[0096] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions described in the foregoing embodiments, or perform equivalent replacements on some or all of the technical features; and these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention, and they should all be covered within the scope of the claims and the description of the present invention.

Claims

1. An industrial data encoding and transmission optimization method based on the industrial Internet of Things, characterized in that Including: Obtain the industrial data to be processed based on the Industrial Internet of Things, obtain the source characteristics corresponding to the industrial data to be processed, and obtain the source length corresponding to the industrial data to be processed according to the source characteristics corresponding to the industrial data to be processed; When the data volume of the industrial data to be processed exceeds the source length, pack the industrial data to be processed to form a data packet to be sent, and obtain the continuously increasing first sequential code corresponding to the current data packet to be sent based on the first coding model; Plan multiple basic transmission paths including different transmission nodes, and obtain the second sequential code corresponding to each basic transmission path based on the position data of multiple transmission nodes in each basic transmission path; Associate the first sequential code and the second sequential code with the data packet to be sent to form a data set to be transmitted, and transmit the data set to be transmitted according to the basic transmission path corresponding to the second sequential code; Receive the data set to be transmitted, obtain the transmission path optimization strategy according to the first sequential code of the received data set to be transmitted, and perform the data transmission of the subsequent data packets to be sent according to the transmission path optimization strategy; The obtaining the transmission path optimization strategy according to the first sequential code of the received data set to be transmitted includes: if the first sequential code of the currently received data set to be transmitted and the first sequential code of the previously received data set to be transmitted are not continuous, and the first sequential code of the currently received data set to be transmitted is greater than the first sequential code of the previously received data set to be transmitted, then obtain the interval difference between the first sequential code of the currently received data set to be transmitted and the first sequential code of the previously received data set to be transmitted; Obtain the maximum interval difference among multiple interval differences within a preset time period, and obtain the second sequential code of the currently received data set to be transmitted corresponding to the maximum interval difference, and use the basic transmission path corresponding to the second sequential code as the optimized transmission path.

2. The industrial data encoding and transmission optimization method based on the industrial Internet of Things according to claim 1, wherein, The performing the data transmission of the subsequent data packets to be sent according to the transmission path optimization strategy includes: Associate the first sequential code with the subsequent data packets to be sent to form a new data set to be transmitted, and transmit the new data set to be transmitted according to the optimized transmission path.

3. The industrial data encoding and transmission optimization method based on the industrial Internet of Things according to claim 1, wherein The obtaining the continuously increasing first sequential code corresponding to the current data packet to be sent based on the first coding model includes: Set the continuous increment value and the initial coding value corresponding to the first formed data packet to be sent; Obtain the number of times the data packet to be sent is formed between the first formed data packet to be sent and the current data packet to be sent; Obtain the continuously increasing first sequential code corresponding to the current data packet to be sent based on the first coding model, the number of times the data packet to be sent is formed, the initial coding value, and the continuous increment value.

4. The industrial data encoding and transmission optimization method based on the industrial Internet of Things according to claim 3, characterized in that, The first coding model in the obtaining the continuously increasing first sequential code corresponding to the current data packet to be sent based on the first coding model, the number of times the data packet to be sent is formed, the initial coding value, and the continuous increment value is expressed as: ; wherein, is the i-th first-order code, is the number of times of forming the data packet to be sent, is the continuous increment value, is the initial code value.

5. The industrial data encoding and transmission optimization method based on the industrial Internet of Things according to claim 1, characterized in that, The obtaining the second sequential code corresponding to each basic transmission path based on the position data of multiple transmission nodes in each basic transmission path includes: Obtain all the transmission nodes in the j-th basic transmission path, and obtain the corresponding unique identifier according to the position data of the obtained transmission nodes; Obtain the second sequence code corresponding to the j-th basic transmission path based on the order of the transmission nodes in the j-th basic transmission path and the unique identifiers corresponding to each transmission node.

6. An industrial data encoding and transmission optimization system based on the industrial Internet of Things, characterized in that, The system includes a management platform, a sensing network platform, and an object platform that are communicatively connected in sequence. The management platform includes: An integrated acquisition module, configured to acquire industrial data to be processed based on the industrial Internet of Things, acquire the source characteristics corresponding to the industrial data to be processed, and obtain the source length corresponding to the industrial data to be processed according to the source characteristics corresponding to the industrial data to be processed; A judgment and sequence coding module, configured to, when the data volume of the industrial data to be processed exceeds the source length, package the industrial data to be processed to form a data packet to be sent, and obtain a continuously increasing first sequence code corresponding to the current data packet to be sent based on the first coding model; A position coding module, configured to plan multiple basic transmission paths including different transmission nodes, and obtain the second sequence code corresponding to each basic transmission path based on the position data of multiple transmission nodes in each basic transmission path; A transmission module, configured to associate the first sequence code and the second sequence code with the data packet to be sent to form a data set to be transmitted, and transmit the data set to be transmitted according to the basic transmission path corresponding to the second sequence code; An optimization module, configured to receive the data set to be transmitted, obtain a transmission path optimization strategy according to the first sequence code of the received data set to be transmitted, and perform data transmission of subsequent data packets to be sent according to the transmission path optimization strategy; The optimization module is further configured to: if the first sequence code of the currently received data set to be transmitted is not continuous with the first sequence code of the previously received data set to be transmitted, and the first sequence code of the currently received data set to be transmitted is greater than the first sequence code of the previously received data set to be transmitted, then obtain the interval difference between the first sequence code of the currently received data set to be transmitted and the first sequence code of the previously received data set to be transmitted; obtain the maximum interval difference among multiple interval differences within a preset time period, and obtain the second sequence code of the currently received data set to be transmitted corresponding to the maximum interval difference, and use the basic transmission path corresponding to the second sequence code as the optimized transmission path; associate the first sequence code with subsequent data packets to be sent to form a new data set to be transmitted, and transmit the new data set to be transmitted according to the optimized transmission path.

7. An electronic device, characterized in that, Including: A memory, on which a computer program is stored; A processor, configured to execute the computer program in the memory to implement the industrial data coding and transmission optimization method based on the industrial Internet of Things according to any one of claims 1 to 5.

8. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that, When the program is executed by the processor, it implements the industrial data coding and transmission optimization method based on the industrial Internet of Things according to any one of claims 1 to 5.

Images