Industrial Internet platform data processing method, device and computer readable medium

Abstract

The embodiment of the present application provides an industrial Internet platform data processing method, device, computer-readable medium and electronic device. The embodiment of the present application first obtains the industrial sensor data to be subjected to data filtering processing; then configures the sequence corresponding to the industrial sensor data into several nodes, so that the nodes are verified, and according to the preset verification method, the nodes that fail to be verified are regarded as invalid nodes, and the nodes that are verified are regarded as valid nodes; the valid nodes are formed into a new sequence, and the new sequence is input into a trained equivalent judgment neural network model, and the valid nodes in the new sequence are grouped into equivalent groups, and a valid node is selected as a representative node in each group; finally, the representative nodes are formed into a storage sequence, and the storage sequence is forwarded to the cloud server for storage, thereby improving the data processing efficiency and reducing the storage space pressure of the cloud server.

Description

[0001] This application is a divisional application of the invention application with an application date of February 21, 2022, Chinese application number 202210155523.8, and invention name “Industrial Internet Platform Data Processing Method, Device and Electronic Equipment”. Technical Field

[0002] The present application relates to the field of computer technology, and more specifically, to an industrial Internet platform data processing method, device, computer-readable medium and electronic device. Background Art

[0003] Industrial real-time data is an important source of data in the industrial Internet. It is usually generated by sensors in industrial systems. Industrial real-time data is generally transmitted to cloud servers via edge devices for unified storage.

[0004] In the traditional industrial Internet, when performing data filtering, a device in the office network obtains all industrial real-time data from the real-time database and performs data filtering based on all industrial real-time data. However, taking an industrial system of a certain scale as an example, there will be about 100,000 sensors, and the industrial real-time data produced every day can reach hundreds of GB. If a device in the office network performs data filtering based on all industrial real-time data, the data processing efficiency will be low. Summary of the invention

[0005] The embodiments of the present application provide an industrial Internet platform data processing method, device, computer-readable medium and electronic device, thereby solving the problem of low data processing efficiency.

[0006] Other features and advantages of the present application will become apparent from the following detailed description, or may be learned in part by the practice of the present application.

[0007] According to one aspect of an embodiment of the present application, an industrial Internet platform data processing method is provided, which is applied to an edge device in the industrial Internet, and the method includes:

[0008] Acquire industrial sensor data to be filtered and processed;

[0009] The sequence corresponding to the industrial sensor data is configured into a plurality of nodes, so that the nodes are verified with each other, and according to a preset verification method, the nodes that fail the verification are regarded as invalid nodes, and the nodes that succeed the verification are regarded as valid nodes;

[0010] Determine a representative node from the valid nodes by using a trained equivalent determination neural network model;

[0011] The representative nodes are organized into a storage sequence, and the storage sequence is forwarded to a cloud server for storage.

[0012] In some embodiments of the present application, based on the aforementioned scheme, the representative node is determined from the valid nodes through the trained equivalence determination neural network model, including: the valid nodes are organized into a new sequence, and the new sequence is input into the trained equivalence determination neural network model, the valid nodes in the new sequence are grouped into equivalent groups, and a valid node is selected from each group as a representative node.

[0013] In some embodiments of the present application, based on the aforementioned solution, the sequence corresponding to the industrial sensor data is configured into a plurality of nodes so that verification is performed between the nodes, and according to a preset verification method, the nodes that fail the verification are regarded as invalid nodes, and the nodes that succeed in the verification are regarded as valid nodes, including:

[0014] A first node receives a first request from a second node, the first request is used to request verification of whether to allow uploading of sensor data of the second node, and the first node and the second node are both industrial sensor data; the first node determines a first verification result based on the identification information of the sensor data corresponding to the second node, the first verification result is used to indicate that uploading of the sensor data corresponding to the second node is allowed, or the first verification result is used to indicate that uploading of the sensor data corresponding to the second node is not allowed, and the identification information of the sensor data corresponding to the second node comes from a node information identification neural network model that is trained on a cloud server and then sent to an edge device; the first node sends the first verification result to the second node; wherein the first node and the second node are adjacent nodes;

[0015] If the first verification result is that uploading the sensor data corresponding to the second node is allowed, the second node is determined to be a valid node; if the first verification result is that uploading the sensor data corresponding to the second node is not allowed, the second node is determined to be an invalid node;

[0016] The first node receives a first request from a third node, the first request is used to request verification of whether to allow uploading of sensor data of the third node, and the first node and the third node are both industrial sensor data; the first node determines a second verification result based on the identification information of the sensor data corresponding to the third node, the second verification result is used to indicate that uploading of the sensor data corresponding to the third node is allowed, or the second verification result is used to indicate that uploading of the sensor data corresponding to the third node is not allowed, and the identification information of the sensor data corresponding to the third node comes from a node information identification neural network model that is trained on a cloud server and then sent to an edge device; the first node sends the second verification result to the third node; wherein the first node and the third node are non-adjacent nodes;

[0017] If the second verification result is that uploading the sensor data corresponding to the third node is allowed, the third node is determined to be a valid node; if the second verification result is that uploading the sensor data corresponding to the third node is not allowed, the third node is determined to be an invalid node; and,

[0018] The second node receives a first request from the first node, the first request is used to request verification whether to allow uploading of sensor data of the first node, and the first node and the second node are both industrial sensor data; the first node determines a first verification result based on the identification information of the sensor data corresponding to the second node, the first verification result is used to indicate that uploading of the sensor data corresponding to the first node is allowed, or the first verification result is used to indicate that uploading of the sensor data corresponding to the first node is not allowed, and the identification information of the sensor data corresponding to the first node comes from a node information identification neural network model that is trained on the cloud server and then sent to the edge device; the second node sends the first verification result to the first node; wherein the first node and the second node are adjacent nodes;

[0019] If the first verification result is that uploading the sensor data corresponding to the second node is not allowed, the second node is determined to be an invalid node; if the first verification result is that uploading the sensor data corresponding to the first node is allowed, the first node sends a request to the third node;

[0020] The third node receives a first request from the first node, the first request is used to request verification whether to allow uploading of sensor data of the first node, and the first node and the third node are both industrial sensor data; the third node determines a second verification result based on the identification information of the sensor data corresponding to the first node, the second verification result is used to indicate that uploading of the sensor data corresponding to the first node is allowed, or the second verification result is used to indicate that uploading of the sensor data corresponding to the first node is not allowed, and the identification information of the sensor data corresponding to the first node comes from a node information identification neural network model that is trained on the cloud server and then sent to the edge device; the first node sends the second verification result to the first node; wherein the first node and the third node are non-adjacent nodes;

[0021] If the second verification result is that uploading the sensor data corresponding to the third node is allowed, the third node is determined to be a valid node; if the second verification result is that uploading the sensor data corresponding to the third node is not allowed, the third node is determined to be an invalid node.

[0022] In some embodiments of the present application, based on the above scheme, the valid nodes are organized into a new sequence, and the new sequence is input into a trained equivalence determination neural network model, the valid nodes in the new sequence are grouped into equivalent groups, and at least one valid node is selected in each group as a representative node, including:

[0023] Input the new sequence composed of valid nodes into the trained equivalence determination neural network model;

[0024] The equivalent determination neural network model judges the valid nodes based on preset dimensions, and uses one or two valid nodes that represent nodes as a valid node group; the preset dimensions include the value of the sensor data, the deviation from the previous sensor, and the absolute value of the deviation of non-adjacent sensors and the probability of the occurrence of the value:

[0025] The valid nodes are grouped based on the valid node group to obtain a plurality of equivalent groups; and a representative node of each equivalent group is determined.

[0026] According to one aspect of an embodiment of the present application, an industrial Internet platform data processing device is provided, including:

[0027] An acquisition module, used to acquire industrial sensor data to be subjected to data filtering processing;

[0028] A verification module, configured to configure the sequence corresponding to the industrial sensor data into a plurality of nodes, so that verification is performed between the nodes, and according to a preset verification method, the nodes that fail the verification are regarded as invalid nodes, and the nodes that succeed the verification are regarded as valid nodes;

[0029] A representative node determination module, used to determine a representative node from the valid nodes by using a trained equivalent determination neural network model;

[0030] The storage module is used to organize the representative nodes into a storage sequence and forward the storage sequence to the cloud server for storage.

[0031] In some embodiments of the present application, based on the above solution, the verification module includes:

[0032] A first verification module is used for a first node to receive a first request from a second node, the first request is used to request verification whether to allow uploading of sensor data of the second node, and the first node and the second node are both industrial sensor data; the first node determines a first verification result based on the identification information of the sensor data corresponding to the second node, the first verification result is used to indicate that uploading of the sensor data corresponding to the second node is allowed, or the first verification result is used to indicate that uploading of the sensor data corresponding to the second node is not allowed, and the identification information of the sensor data corresponding to the second node comes from a node information identification neural network model that is trained on a cloud server and then sent to an edge device; the first node sends the first verification result to the second node; wherein the first node and the second node are adjacent nodes;

[0033] A first judgment module, configured to determine that the second node is a valid node if the first verification result is that uploading of the sensor data corresponding to the second node is allowed; and to determine that the second node is an invalid node if the first verification result is that uploading of the sensor data corresponding to the second node is not allowed;

[0034] A second verification module is used for a first node to receive a first request from a third node, the first request is used to request verification whether to allow uploading of sensor data of the third node, and the first node and the third node are both industrial sensor data; the first node determines a second verification result based on the identification information of the sensor data corresponding to the third node, the second verification result is used to indicate that uploading of the sensor data corresponding to the third node is allowed, or the second verification result is used to indicate that uploading of the sensor data corresponding to the third node is not allowed, and the identification information of the sensor data corresponding to the third node comes from a node information identification neural network model that is trained on the cloud server and then sent to the edge device; the first node sends the second verification result to the third node; wherein the first node and the third node are non-adjacent nodes;

[0035] A second judgment module, configured to determine that the third node is a valid node if the second verification result is that uploading of the sensor data corresponding to the third node is allowed; and determine that the third node is an invalid node if the second verification result is that uploading of the sensor data corresponding to the third node is not allowed;

[0036] A third verification module is used for the second node to receive a first request from the first node, the first request is used to request verification whether to allow uploading of sensor data of the first node, and the first node and the second node are both industrial sensor data; the first node determines a first verification result based on the identification information of the sensor data corresponding to the second node, the first verification result is used to indicate that uploading of the sensor data corresponding to the first node is allowed, or the first verification result is used to indicate that uploading of the sensor data corresponding to the first node is not allowed, and the identification information of the sensor data corresponding to the first node comes from a node information identification neural network model that is trained on the cloud server and then sent to the edge device; the second node sends the first verification result to the first node; wherein the first node and the second node are adjacent nodes;

[0037] a third judgment module, configured to determine that the second node is an invalid node if the first verification result is that uploading of the sensor data corresponding to the second node is not allowed; and the first node sends a request to the third node if the first verification result is that uploading of the sensor data corresponding to the first node is allowed;

[0038] A fourth verification module is used for the third node to receive a first request from the first node, the first request is used to request verification whether to allow uploading of sensor data of the first node, and the first node and the third node are both industrial sensor data; the third node determines a second verification result based on the identification information of the sensor data corresponding to the first node, the second verification result is used to indicate that uploading of the sensor data corresponding to the first node is allowed, or the second verification result is used to indicate that uploading of the sensor data corresponding to the first node is not allowed, and the identification information of the sensor data corresponding to the first node comes from a node information identification neural network model that is trained on the cloud server and then sent to the edge device; the first node sends the second verification result to the first node; wherein the first node and the third node are non-adjacent nodes;

[0039] The fourth judgment module is used to determine that the third node is a valid node if the second verification result is that uploading the sensor data corresponding to the third node is allowed; if the second verification result is that uploading the sensor data corresponding to the third node is not allowed, then determine that the third node is an invalid node.

[0040] According to one aspect of an embodiment of the present application, a computer-readable medium is provided, on which a computer program is stored, wherein when the computer program is executed by a processor, the following method is implemented:

[0041] Acquire industrial sensor data to be filtered and processed;

[0042] The sequence corresponding to the industrial sensor data is configured into a plurality of nodes, so that the nodes are verified with each other, and according to a preset verification method, the nodes that fail the verification are regarded as invalid nodes, and the nodes that succeed the verification are regarded as valid nodes;

[0043] Determine a representative node from the valid nodes by using a trained equivalent determination neural network model;

[0044] The representative nodes are organized into a storage sequence, and the storage sequence is forwarded to a cloud server for storage.

[0045] According to one aspect of an embodiment of the present application, there is provided an electronic device, characterized in that it includes:

[0046] one or more processors;

[0047] A storage device, used to store one or more programs, when the one or more programs are executed by the one or more processors, enables the one or more processors to implement the following method:

[0048] Acquire industrial sensor data to be filtered and processed;

[0049] The sequence corresponding to the industrial sensor data is configured into a plurality of nodes, so that the nodes are verified with each other, and according to a preset verification method, the nodes that fail the verification are regarded as invalid nodes, and the nodes that succeed the verification are regarded as valid nodes;

[0050] Determine a representative node from the valid nodes by using a trained equivalent determination neural network model;

[0051] The representative nodes are organized into a storage sequence, and the storage sequence is forwarded to a cloud server for storage.

[0052] In the technical solutions provided in some embodiments of the present application, the industrial sensor data to be subjected to data filtering processing is first acquired; then the sequence corresponding to the industrial sensor data is configured into a number of nodes so that verification is performed between the nodes, and according to a preset verification method, the nodes for which the verification fails are regarded as invalid nodes, and the nodes for which the verification succeeds are regarded as valid nodes; representative nodes are determined from the valid nodes through a trained equivalent determination neural network model; finally, the representative nodes are organized into a storage sequence, and the storage sequence is forwarded to a cloud server for storage, thereby improving data processing efficiency and reducing storage space pressure on the cloud server.

[0053] It should be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0054] The drawings herein are incorporated into the specification and constitute a part of the specification, illustrate embodiments consistent with the present application, and together with the specification are used to explain the principles of the present application. Obviously, the drawings described below are only some embodiments of the present application, and for ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0055] Figure 1 A flow chart of an industrial Internet platform data processing method to which the technical solution of an embodiment of the present application can be applied is shown;

[0056] Figure 2 A schematic diagram of an industrial Internet platform data processing device according to an embodiment of the present application is schematically shown;

[0057] Figure 3 A schematic diagram of a verification module according to an embodiment of the present application is schematically shown;

[0058] Figure 4 Another schematic diagram of a verification module according to an embodiment of the present application is schematically shown;

[0059] Figure 5 Another schematic diagram schematically shows a verification module according to an embodiment of the present application;

[0060] Figure 6 A schematic diagram of the structure of a computer system suitable for implementing an electronic device of an embodiment of the present application is shown. DETAILED DESCRIPTION

[0061] Example embodiments will now be described more fully with reference to the accompanying drawings. However, example embodiments can be implemented in a variety of forms and should not be construed as limited to the examples set forth herein; rather, these embodiments are provided so that this application will be more comprehensive and complete and fully convey the concept of the example embodiments to those skilled in the art.

[0062] In addition, described feature, structure or characteristic can be combined in one or more embodiments in any suitable manner. In the following description, many specific details are provided to provide a full understanding of the embodiments of the present application. However, those skilled in the art will appreciate that the technical scheme of the present application can be put into practice without one or more of the specific details, or other methods, components, devices, steps, etc. can be adopted. In other cases, known methods, devices, realizations or operations are not shown or described in detail to avoid blurring the various aspects of the application.

[0063] The block diagrams shown in the accompanying drawings are merely functional entities and do not necessarily correspond to physically independent entities. That is, these functional entities may be implemented in software form, or in one or more hardware modules or integrated circuits, or in different networks and / or processor devices and / or microcontroller devices.

[0064] The flowcharts shown in the accompanying drawings are only exemplary and do not necessarily include all the contents and operations / steps, nor must they be executed in the order described. For example, some operations / steps can be decomposed, and some operations / steps can be combined or partially combined, so the actual execution order may change according to actual conditions.

[0065] As some embodiments of the present invention, Figure 1 A flow chart of a method for processing data on an industrial Internet platform is shown. The method for processing data on an industrial Internet platform is applied to edge devices in the industrial Internet, and the method includes:

[0066] S101: Acquire industrial sensor data to be subjected to data filtering processing.

[0067] Among them, industrial sensor data includes data from various sensors, where the types of sensors include but are not limited to temperature sensors, humidity sensors, voltage sensors, current sensors, pressure sensors, light sensors, acceleration sensors, and angular velocity sensors. In order to achieve unified management of various sensors, "sensor channels" can be defined. Specifically, one sensor channel is used to complete the collection of one physical signal, and the system assigns a unique ID to each sensor channel. When you need to obtain sensor data, just call the function interface for obtaining sensor data in the application.

[0068] S102: configuring the sequence corresponding to the industrial sensor data into a plurality of nodes so that verification is performed between the nodes, and according to a preset verification method, treating nodes that fail verification as invalid nodes and treating nodes that succeed verification as valid nodes.

[0069] S103: The valid nodes are organized into a new sequence, and the new sequence is input into a trained equivalence determination neural network model, the valid nodes in the new sequence are grouped into equivalent groups, and a valid node is selected from each group as a representative node.

[0070] For S102 and S103, the purpose is to find out the representative node, that is, the effective and representative sensor data.

[0071] S104: Group the representative nodes into a storage sequence, and forward the storage sequence to a cloud server for storage.

[0072] In this step, the cloud server can centrally process the sensor data in the storage sequence. Due to the processing in S01 and S103, the magnitude of the sensor data is greatly reduced, which effectively improves the data processing efficiency.

[0073] In the technical solutions provided in some embodiments of the present application, the industrial sensor data to be subjected to data filtering processing is first acquired; then the sequence corresponding to the industrial sensor data is configured into a number of nodes, so that verification is performed between the nodes, and according to a preset verification method, the nodes for which the verification fails are regarded as invalid nodes, and the nodes for which the verification succeeds are regarded as valid nodes; the valid nodes are organized into a new sequence, and the new sequence is input into a trained equivalence determination neural network model, the valid nodes in the new sequence are grouped into equivalent groups, and a valid node is selected from each group as a representative node; finally, the representative nodes are organized into a storage sequence, and the storage sequence is forwarded to a cloud server for storage, thereby improving the data processing efficiency and reducing the storage space pressure of the cloud server.

[0074] In some embodiments of the present application, based on the above solution, S102 specifically includes:

[0075] S201: A first node receives a first request from a second node, the first request being used to request verification of whether to allow uploading of sensor data of the second node, the first node and the second node both being industrial sensor data; the first node determines a first verification result based on identification information of the sensor data corresponding to the second node, the first verification result being used to indicate that uploading of the sensor data corresponding to the second node is allowed, or the first verification result being used to indicate that uploading of the sensor data corresponding to the second node is not allowed, the identification information of the sensor data corresponding to the second node being from a node information identification neural network model trained on a cloud server and then sent to an edge device; the first node sends the first verification result to the second node; wherein the first node and the second node are adjacent nodes;

[0076] S202: If the first verification result is that uploading the sensor data corresponding to the second node is allowed, the second node is determined to be a valid node; if the first verification result is that uploading the sensor data corresponding to the second node is not allowed, the second node is determined to be an invalid node;

[0077] S203: The first node receives a first request from a third node, the first request is used to request verification of whether to allow uploading of sensor data of the third node, and the first node and the third node are both industrial sensor data; the first node determines a second verification result based on the identification information of the sensor data corresponding to the third node, the second verification result is used to indicate that uploading of the sensor data corresponding to the third node is allowed, or the second verification result is used to indicate that uploading of the sensor data corresponding to the third node is not allowed, and the identification information of the sensor data corresponding to the third node comes from a node information identification neural network model that is trained on the cloud server and then sent to the edge device; the first node sends the second verification result to the third node; wherein the first node and the third node are non-adjacent nodes;

[0078] S204: If the second verification result is that uploading the sensor data corresponding to the third node is allowed, the third node is determined to be a valid node; if the second verification result is that uploading the sensor data corresponding to the third node is not allowed, the third node is determined to be an invalid node.

[0079] In some embodiments of the present application, based on the above solution, S102 specifically includes:

[0080] S301: The second node receives a first request from the first node, the first request is used to request verification whether uploading of sensor data of the first node is allowed, and the first node and the second node are both industrial sensor data; the first node determines a first verification result based on the identification information of the sensor data corresponding to the second node, the first verification result is used to indicate that uploading of the sensor data corresponding to the first node is allowed, or the first verification result is used to indicate that uploading of the sensor data corresponding to the first node is not allowed, and the identification information of the sensor data corresponding to the first node comes from a node information identification neural network model that is trained on the cloud server and then sent to the edge device; the second node sends the first verification result to the first node; wherein the first node and the second node are adjacent nodes.

[0081] S302: If the first verification result is that uploading the sensor data corresponding to the second node is not allowed, the second node is determined to be an invalid node; if the first verification result is that uploading the sensor data corresponding to the first node is allowed, the first node sends a request to the third node.

[0082] S303: The third node receives a first request from the first node, the first request is used to request verification whether uploading of sensor data of the first node is allowed, and the first node and the third node are both industrial sensor data; the third node determines a second verification result based on the identification information of the sensor data corresponding to the first node, the second verification result is used to indicate that uploading of the sensor data corresponding to the first node is allowed, or the second verification result is used to indicate that uploading of the sensor data corresponding to the first node is not allowed, and the identification information of the sensor data corresponding to the first node comes from a node information identification neural network model that is trained on the cloud server and then sent to the edge device; the first node sends the second verification result to the first node; wherein the first node and the third node are non-adjacent nodes.

[0083] S304: If the second verification result is that uploading the sensor data corresponding to the third node is allowed, the third node is determined to be a valid node; if the second verification result is that uploading the sensor data corresponding to the third node is not allowed, the third node is determined to be an invalid node.

[0084] As some embodiments of the present application, based on the above solution, S102 specifically includes:

[0085] S401: A first node receives a first request from a second node, wherein the first request is used to request verification of whether uploading of sensor data of the second node is allowed, and both the first node and the second node are industrial sensor data; the first node determines a first verification result based on identification information of the sensor data corresponding to the second node, wherein the first verification result is used to indicate that uploading of the sensor data corresponding to the second node is allowed, or the first verification result is used to indicate that uploading of the sensor data corresponding to the second node is not allowed, and the identification information of the sensor data corresponding to the second node comes from a node information identification neural network model trained on the cloud server and then sent to the edge device; the first node sends the first verification result to the second node; wherein the first node and the second node are adjacent nodes.

[0086] S402: If the first verification result is that uploading the sensor data corresponding to the second node is allowed, the second node is determined to be a valid node; if the first verification result is that uploading the sensor data corresponding to the second node is not allowed, the second node is determined to be an invalid node.

[0087] S403: The first node receives a first request from a third node, the first request is used to request verification of whether uploading sensor data of the third node is allowed, and the first node and the third node are both industrial sensor data; the first node determines a second verification result based on the identification information of the sensor data corresponding to the third node, the second verification result is used to indicate that uploading of the sensor data corresponding to the third node is allowed, or the second verification result is used to indicate that uploading of the sensor data corresponding to the third node is not allowed, and the identification information of the sensor data corresponding to the third node comes from a node information identification neural network model that is trained on the cloud server and then sent to the edge device; the first node sends the second verification result to the third node; wherein the first node and the third node are non-adjacent nodes.

[0088] S404: If the second verification result is that uploading the sensor data corresponding to the third node is allowed, the third node is determined to be a valid node; if the second verification result is that uploading the sensor data corresponding to the third node is not allowed, the third node is determined to be an invalid node.

[0089] S405: The second node receives a first request from the first node, the first request is used to request verification whether uploading of sensor data of the first node is allowed, and the first node and the second node are both industrial sensor data; the first node determines a first verification result based on the identification information of the sensor data corresponding to the second node, the first verification result is used to indicate that uploading of the sensor data corresponding to the first node is allowed, or the first verification result is used to indicate that uploading of the sensor data corresponding to the first node is not allowed, and the identification information of the sensor data corresponding to the first node comes from a node information identification neural network model that is trained on the cloud server and then sent to the edge device; the second node sends the first verification result to the first node; wherein, the first node and the second node are adjacent nodes.

[0090] S406: If the first verification result is that uploading the sensor data corresponding to the second node is not allowed, the second node is determined to be an invalid node; if the first verification result is that uploading the sensor data corresponding to the first node is allowed, the first node sends a request to the third node.

[0091] S407: The third node receives a first request from the first node, the first request is used to request verification whether uploading of sensor data of the first node is allowed, and the first node and the third node are both industrial sensor data; the third node determines a second verification result based on the identification information of the sensor data corresponding to the first node, the second verification result is used to indicate that uploading of the sensor data corresponding to the first node is allowed, or the second verification result is used to indicate that uploading of the sensor data corresponding to the first node is not allowed, and the identification information of the sensor data corresponding to the first node comes from a node information identification neural network model trained on the cloud server and then sent to the edge device; the first node sends the second verification result to the first node; wherein the first node and the third node are non-adjacent nodes.

[0092] S408: If the second verification result is that uploading the sensor data corresponding to the third node is allowed, the third node is determined to be a valid node; if the second verification result is that uploading the sensor data corresponding to the third node is not allowed, the third node is determined to be an invalid node.

[0093] In this embodiment, the four steps S401-S404 and S405-S408 are processed in parallel. In other words, the first node and the second node are cross-validated, which further ensures the accuracy of the verification. At the same time, due to the parallel verification and calculation, the calculation efficiency is not reduced.

[0094] In some embodiments of the present application, based on the above solution, S103 specifically includes:

[0095] S501: Input a new sequence consisting of valid nodes into the trained equivalence determination neural network model.

[0096] S502: The equivalent determination neural network model judges the valid nodes based on preset dimensions, and uses one or two valid nodes representing the nodes as a valid node group; the preset dimensions include the value of the sensor data, the deviation from the previous sensor, the absolute value of the deviation of the non-adjacent sensor, and the probability of the occurrence of the value.

[0097] S503: Grouping the valid nodes based on the valid node group to obtain a plurality of equivalent groups; and determining a representative node of each equivalent group.

[0098] In some embodiments of the present application, based on the above solution, S102 specifically includes:

[0099] S601: Calculate the probability that the current node is a valid node by the following formula;

[0100]

[0101] Among them, P is the probability that the current node is a valid node, P xl_n is the probability that the adjacent nodes of the nth node are invalid nodes, P fxl_n is the probability that the non-adjacent nodes of the nth node are invalid nodes, W xl_n and W fxl_n are the preset weights, and W xl_n +W fxl_n =1, 1≤n≤N, N is the total number of sensor nodes.

[0102] S602: If the probability that the current node is a valid node is greater than a preset threshold, it is determined that the current node verification is established; if the probability that the current node is a valid node is less than or equal to the preset threshold, it is determined that the current node verification is not established.

[0103] S603: Nodes for which verification fails are regarded as invalid nodes, and nodes for which verification succeeds are regarded as valid nodes.

[0104] As some embodiments of the present application, Figure 2 As shown, an industrial Internet platform data processing device 10 is provided. The industrial Internet platform data processing device 10 includes an acquisition module 11, a verification module 12, a representative node determination module 13 and a storage module 14.

[0105] Among them, the acquisition module 11 is used to acquire the industrial sensor data to be subjected to data filtering processing; the verification module 12 is used to configure the sequence corresponding to the industrial sensor data into a plurality of nodes so that verification is performed between the nodes, and according to a preset verification method, the nodes that fail the verification are regarded as invalid nodes, and the nodes that succeed in the verification are regarded as valid nodes; the representative node determination module 13 is used to form the valid nodes into a new sequence, and input the new sequence into a trained equivalent judgment neural network model, and group the valid nodes in the new sequence into equivalent groups, and select a valid node in each group as a representative node; the storage module 14 is used to form the representative nodes into a storage sequence, and forward the storage sequence to a cloud server for storage.

[0106] As some embodiments of the present application, Figure 3 As shown, a schematic diagram of the verification module 12 is provided. The verification module 12 includes a first verification module 121, a first judgment module 122, a second verification module 123 and a second judgment module 124.

[0107] Among them, the first verification module 121 is used for the first node to receive a first request from the second node, the first request is used to request verification whether to allow uploading of sensor data of the second node, and the first node and the second node are both industrial sensor data; the first node determines a first verification result based on the identification information of the sensor data corresponding to the second node, and the first verification result is used to indicate that uploading of the sensor data corresponding to the second node is allowed, or the first verification result is used to indicate that uploading of the sensor data corresponding to the second node is not allowed, and the identification information of the sensor data corresponding to the second node comes from a node information identification neural network model that is trained on the cloud server side and then sent to the edge device; the first node sends the first verification result to the second node; wherein the first node and the second node are adjacent nodes.

[0108] The first judgment module 122 is used to determine that the second node is a valid node if the first verification result is that uploading the sensor data corresponding to the second node is allowed; if the first verification result is that uploading the sensor data corresponding to the second node is not allowed, determine that the second node is an invalid node.

[0109] The second verification module 123 is used for the first node to receive a first request from the third node, the first request is used to request verification whether to allow uploading of sensor data of the third node, and the first node and the third node are both industrial sensor data; the first node determines a second verification result based on the identification information of the sensor data corresponding to the third node, and the second verification result is used to indicate that uploading of the sensor data corresponding to the third node is allowed, or the second verification result is used to indicate that uploading of the sensor data corresponding to the third node is not allowed, and the identification information of the sensor data corresponding to the third node comes from a node information identification neural network model that is trained on the cloud server side and then sent to the edge device; the first node sends the second verification result to the third node; wherein the first node and the third node are non-adjacent nodes.

[0110] The second judgment module 124 is used to determine that the third node is a valid node if the second verification result is that uploading the sensor data corresponding to the third node is allowed; if the second verification result is that uploading the sensor data corresponding to the third node is not allowed, then determine that the third node is an invalid node.

[0111] As some embodiments of the present application, Figure 4 As shown, a schematic diagram of the verification module 12 is provided. The verification module 12 includes a third verification module 125, a third judgment module 126, a fourth verification module 127 and a fourth judgment module 128.

[0112] The third verification module 125 is used for the second node to receive a first request from the first node, the first request is used to request verification whether to allow uploading of sensor data of the first node, and the first node and the second node are both industrial sensor data; the first node determines a first verification result based on the identification information of the sensor data corresponding to the second node, and the first verification result is used to indicate that uploading of the sensor data corresponding to the first node is allowed, or the first verification result is used to indicate that uploading of the sensor data corresponding to the first node is not allowed, and the identification information of the sensor data corresponding to the first node comes from a node information identification neural network model that is trained on the cloud server side and then sent to the edge device; the second node sends the first verification result to the first node; wherein the first node and the second node are adjacent nodes.

[0113] The third judgment module 126 is used to determine that the second node is an invalid node if the first verification result is that uploading the sensor data corresponding to the second node is not allowed; if the first verification result is that uploading the sensor data corresponding to the first node is allowed, the first node sends a request to the third node.

[0114] The fourth verification module 127 is used for the third node to receive a first request from the first node, the first request is used to request verification whether uploading of sensor data of the first node is allowed, and the first node and the third node are both industrial sensor data; the third node determines a second verification result based on the identification information of the sensor data corresponding to the first node, the second verification result is used to indicate that uploading of the sensor data corresponding to the first node is allowed, or the second verification result is used to indicate that uploading of the sensor data corresponding to the first node is not allowed, and the identification information of the sensor data corresponding to the first node comes from a node information identification neural network model that is trained on the cloud server side and then sent to the edge device; the first node sends the second verification result to the first node; wherein the first node and the third node are non-adjacent nodes.

[0115] The fourth judgment module 128 is used to determine that the third node is a valid node if the second verification result is that uploading the sensor data corresponding to the third node is allowed; if the second verification result is that uploading the sensor data corresponding to the third node is not allowed, then determine that the third node is an invalid node.

[0116] As some embodiments of the present application, Figure 5As shown, a schematic diagram of the verification module 12 is provided. The verification module 12 includes a first verification module 121, a first judgment module 122, a second verification module 123, a second judgment module 124, a third verification module 125, a third judgment module 126, a fourth verification module 127 and a fourth judgment module 128.

[0117] Among them, the first verification module 121 is used for the first node to receive a first request from the second node, the first request is used to request verification whether to allow uploading of sensor data of the second node, and the first node and the second node are both industrial sensor data; the first node determines a first verification result based on the identification information of the sensor data corresponding to the second node, and the first verification result is used to indicate that uploading of the sensor data corresponding to the second node is allowed, or the first verification result is used to indicate that uploading of the sensor data corresponding to the second node is not allowed, and the identification information of the sensor data corresponding to the second node comes from a node information identification neural network model that is trained on the cloud server and then sent to the edge device; the first node sends the first verification result to the second node; wherein the first node and the second node are adjacent nodes;

[0118] A first judgment module 122 is configured to determine that the second node is a valid node if the first verification result is that uploading of the sensor data corresponding to the second node is allowed; and determine that the second node is an invalid node if the first verification result is that uploading of the sensor data corresponding to the second node is not allowed;

[0119] The second verification module 123 is used for the first node to receive a first request from the third node, the first request is used to request verification whether to allow uploading of sensor data of the third node, and the first node and the third node are both industrial sensor data; the first node determines a second verification result based on the identification information of the sensor data corresponding to the third node, the second verification result is used to indicate that uploading of the sensor data corresponding to the third node is allowed, or the second verification result is used to indicate that uploading of the sensor data corresponding to the third node is not allowed, and the identification information of the sensor data corresponding to the third node comes from a node information identification neural network model that is trained on the cloud server and then sent to the edge device; the first node sends the second verification result to the third node; wherein the first node and the third node are non-adjacent nodes;

[0120] The second judgment module 124 is used to determine that the third node is a valid node if the second verification result is that uploading the sensor data corresponding to the third node is allowed; if the second verification result is that uploading the sensor data corresponding to the third node is not allowed, then determine that the third node is an invalid node.

[0121] The third verification module 125 is used for the second node to receive a first request from the first node, the first request is used to request verification whether to allow uploading of sensor data of the first node, and the first node and the second node are both industrial sensor data; the first node determines a first verification result based on the identification information of the sensor data corresponding to the second node, the first verification result is used to indicate that uploading of the sensor data corresponding to the first node is allowed, or the first verification result is used to indicate that uploading of the sensor data corresponding to the first node is not allowed, and the identification information of the sensor data corresponding to the first node comes from a node information identification neural network model that is trained on the cloud server and then sent to the edge device; the second node sends the first verification result to the first node; wherein the first node and the second node are adjacent nodes;

[0122] A third judgment module 126 is configured to determine that the second node is an invalid node if the first verification result is that uploading of the sensor data corresponding to the second node is not allowed; if the first verification result is that uploading of the sensor data corresponding to the first node is allowed, the first node sends a request to the third node;

[0123] The fourth verification module 127 is used for the third node to receive a first request from the first node, the first request is used to request verification whether to allow uploading of sensor data of the first node, and the first node and the third node are both industrial sensor data; the third node determines a second verification result based on the identification information of the sensor data corresponding to the first node, the second verification result is used to indicate that uploading of the sensor data corresponding to the first node is allowed, or the second verification result is used to indicate that uploading of the sensor data corresponding to the first node is not allowed, and the identification information of the sensor data corresponding to the first node comes from a node information identification neural network model that is trained on the cloud server and then sent to the edge device; the first node sends the second verification result to the first node; wherein the first node and the third node are non-adjacent nodes;

[0124] The fourth judgment module 128 is used to determine that the third node is a valid node if the second verification result is that uploading the sensor data corresponding to the third node is allowed; if the second verification result is that uploading the sensor data corresponding to the third node is not allowed, then determine that the third node is an invalid node.

[0125] According to one aspect of an embodiment of the present application, a computer-readable medium is provided, on which a computer program is stored, wherein when the computer program is executed by a processor, the following method is implemented:

[0126] Acquire industrial sensor data to be filtered and processed;

[0127] The sequence corresponding to the industrial sensor data is configured into a plurality of nodes, so that the nodes are verified with each other, and according to a preset verification method, the nodes that fail the verification are regarded as invalid nodes, and the nodes that succeed the verification are regarded as valid nodes;

[0128] The valid nodes are grouped into a new sequence, and the new sequence is input into a trained equivalent judgment neural network model, the valid nodes in the new sequence are grouped equivalently, and a valid node is selected from each group as a representative node;

[0129] The representative nodes are organized into a storage sequence, and the storage sequence is forwarded to a cloud server for storage.

[0130] According to one aspect of an embodiment of the present application, there is provided an electronic device, characterized in that it includes:

[0131] one or more processors;

[0132] A storage device, used to store one or more programs, when the one or more programs are executed by the one or more processors, enables the one or more processors to implement the following method:

[0133] Acquire industrial sensor data to be filtered and processed;

[0134] The sequence corresponding to the industrial sensor data is configured into a plurality of nodes, so that the nodes are verified with each other, and according to a preset verification method, the nodes that fail the verification are regarded as invalid nodes, and the nodes that succeed the verification are regarded as valid nodes;

[0135] The valid nodes are grouped into a new sequence, and the new sequence is input into a trained equivalent judgment neural network model, the valid nodes in the new sequence are grouped equivalently, and a valid node is selected from each group as a representative node;

[0136] The representative nodes are organized into a storage sequence, and the storage sequence is forwarded to a cloud server for storage.

[0137] Figure 6 A schematic diagram of the structure of a computer system suitable for implementing an electronic device of an embodiment of the present application is shown.

[0138] It should be noted that Figure 6 The computer system 600 of the electronic device shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present application.

[0139] like Figure 6As shown, the computer system 600 includes a central processing unit (CPU) 601, which can perform various appropriate actions and processes according to the program stored in the read-only memory (ROM) 602 or the program loaded from the storage part 608 to the random access memory (RAM) 603, such as executing the method described in the above embodiment. In the RAM 603, various programs and data required for system operation are also stored. The CPU 601, the ROM 602 and the RAM 603 are connected to each other via a bus 606. An input / output (I / O) interface 606 is also connected to the bus 606.

[0140] The following components are connected to the I / O interface 606: an input section 606 including a keyboard, a mouse, etc.; an output section 607 including a cathode ray tube (CRT), a liquid crystal display (LCD), etc., and a speaker, etc.; a storage section 608 including a hard disk, etc.; and a communication section 609 including a network interface card such as a LAN (Local Area Network) card, a modem, etc. The communication section 609 performs communication processing via a network such as the Internet. A drive 610 is also connected to the I / O interface 606 as needed. A removable medium 611, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., is installed on the drive 610 as needed so that a computer program read therefrom is installed into the storage section 608 as needed.

[0141] In particular, according to an embodiment of the present application, the process described above with reference to the flowchart can be implemented as a computer software program. For example, an embodiment of the present application includes a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program includes a computer program for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network through a communication section 609, and / or installed from a removable medium 611. When the computer program is executed by a central processing unit (CPU) 601, various functions defined in the system of the present application are executed.

[0142] It should be noted that the computer-readable medium shown in the embodiment of the present application may be a computer-readable signal medium or a computer-readable storage medium or any combination of the above two. The computer-readable storage medium may be, for example, - but not limited to - an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM), a flash memory, an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the present application, a computer-readable storage medium may be any tangible medium containing or storing a program, which may be used by an instruction execution system, device or device or used in combination with it. In the present application, a computer-readable signal medium may include a data signal propagated in a baseband or as part of a carrier wave, wherein a computer-readable computer program is carried. Such propagated data signals may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. Computer-readable signal media may also be any computer-readable medium other than computer-readable storage media, which may send, propagate, or transmit programs for use by or in conjunction with an instruction execution system, apparatus, or device. The computer program contained on the computer-readable medium may be transmitted using any appropriate medium, including but not limited to: wireless, wired, etc., or any suitable combination of the above.

[0143] The flowchart and block diagram in the accompanying drawings illustrate the possible architecture, functions and operations of the system, method and computer program product according to various embodiments of the present application. Wherein, each box in the flowchart or block diagram can represent a module, a program segment, or a part of the code, and the above-mentioned module, program segment, or a part of the code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order from the order marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram or flowchart, and the combination of boxes in the block diagram or flowchart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0144] The units involved in the embodiments described in this application may be implemented by software or hardware, and the units described may also be set in a processor. The names of these units do not, in some cases, constitute limitations on the units themselves.

[0145] According to one aspect of the present application, a computer program product or a computer program is provided, the computer program product or the computer program comprising computer instructions, the computer instructions being stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium, and the processor executes the computer instructions, so that the computer device executes the methods provided in the above-mentioned various optional implementations.

[0146] As another aspect, the present application also provides a computer-readable medium, which may be included in the electronic device described in the above embodiment; or may exist independently without being assembled into the electronic device. The above computer-readable medium carries one or more programs, and when the above one or more programs are executed by an electronic device, the electronic device implements the method described in the above embodiment.

[0147] It should be noted that, although several modules or units of the equipment for action execution are mentioned in the above detailed description, this division is not mandatory. In fact, according to the embodiments of the present application, the features and functions of two or more modules or units described above can be embodied in one module or unit. On the contrary, the features and functions of one module or unit described above can be further divided into being embodied by multiple modules or units.

[0148] Through the description of the above implementation methods, it is easy for those skilled in the art to understand that the example implementation methods described here can be implemented by software or by combining software with necessary hardware. Therefore, the technical solution according to the implementation methods of the present application can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (which can be a CD-ROM, a USB flash drive, a mobile hard disk, etc.) or on a network, and includes several instructions to enable a computing device (which can be a personal computer, a server, a touch terminal, or a network device, etc.) to execute the method according to the implementation methods of the present application.

[0149] Those skilled in the art will readily appreciate other embodiments of the present application after considering the specification and practicing the embodiments disclosed herein. The present application is intended to cover any variations, uses or adaptations of the present application, which follow the general principles of the present application and include common knowledge or customary technical means in the art that are not disclosed in the present application.

[0150] It should be understood that the present application is not limited to the precise structures that have been described above and shown in the drawings, and that various modifications and changes may be made without departing from the scope thereof. The scope of the present application is limited only by the appended claims.

Claims

1. A method for processing data on an industrial Internet platform, characterized in that: Applied to edge devices in the industrial Internet, the method includes: Acquire industrial sensor data to be filtered and processed; The sequence corresponding to the industrial sensor data is configured into a plurality of nodes, so that the nodes are verified with each other, and according to a preset verification method, the nodes that fail the verification are regarded as invalid nodes, and the nodes that succeed the verification are regarded as valid nodes; Determine a representative node from the valid nodes by using a trained equivalent determination neural network model; The representative nodes are organized into a storage sequence, and the storage sequence is forwarded to a cloud server for storage; Wherein, determining the representative node from the valid nodes by using the trained equivalent determination neural network model includes: The valid nodes are grouped into a new sequence, and the new sequence is input into a trained equivalent judgment neural network model, the valid nodes in the new sequence are grouped equivalently, and a valid node is selected from each group as a representative node; The configuring of the sequence corresponding to the industrial sensor data into a plurality of nodes so that the nodes are verified with each other, and according to a preset verification method, the nodes that fail the verification are regarded as invalid nodes, and the nodes that succeed the verification are regarded as valid nodes, including: A first node receives a first request from a second node, the first request being used to request verification of whether uploading sensor data of the second node is allowed; the first node determines a first verification result based on identification information of the sensor data corresponding to the second node, the first verification result being used to indicate that uploading of the sensor data corresponding to the second node is allowed, or the first verification result being used to indicate that uploading of the sensor data corresponding to the second node is not allowed, the identification information of the sensor data corresponding to the second node being from a node information identification neural network model trained on a cloud server and then sent to an edge device; the first node sends the first verification result to the second node; wherein the first node and the second node are adjacent nodes; If the first verification result is that uploading the sensor data corresponding to the second node is allowed, the second node is determined to be a valid node; if the first verification result is that uploading the sensor data corresponding to the second node is not allowed, the second node is determined to be an invalid node; The first node receives a first request from a third node, the first request is used to request verification of whether to allow uploading of sensor data of the third node, and the first node and the third node are both industrial sensor data; the first node determines a second verification result based on the identification information of the sensor data corresponding to the third node, the second verification result is used to indicate that uploading of the sensor data corresponding to the third node is allowed, or the second verification result is used to indicate that uploading of the sensor data corresponding to the third node is not allowed, and the identification information of the sensor data corresponding to the third node comes from a node information identification neural network model that is trained on a cloud server and then sent to an edge device; the first node sends the second verification result to the third node; wherein the first node and the third node are non-adjacent nodes; If the second verification result is that uploading the sensor data corresponding to the third node is allowed, the third node is determined to be a valid node; if the second verification result is that uploading the sensor data corresponding to the third node is not allowed, the third node is determined to be an invalid node.

2. The industrial Internet platform data processing method according to claim 1, characterized in that: The valid nodes are formed into a new sequence, and the new sequence is input into a trained equivalent determination neural network model, the valid nodes in the new sequence are equivalently grouped, and at least one valid node in each group is selected as a representative node, including: Input the new sequence composed of valid nodes into the trained equivalence determination neural network model; The equivalent determination neural network model judges the valid nodes based on preset dimensions, and uses one or two valid nodes that can represent nodes as a valid node group; the preset dimensions include the value of the sensor data, the deviation from the previous sensor, and the absolute value of the deviation of non-adjacent sensors and the probability of the occurrence of the value; The valid nodes are grouped based on the valid node group to obtain a plurality of equivalent groups; and a representative node of each equivalent group is determined.

3. An industrial Internet platform data processing device, characterized in that: The device comprises: An acquisition module, used to acquire industrial sensor data to be subjected to data filtering processing; A verification module, configured to configure the sequence corresponding to the industrial sensor data into a plurality of nodes, so that verification is performed between the nodes, and according to a preset verification method, the nodes that fail the verification are regarded as invalid nodes, and the nodes that succeed the verification are regarded as valid nodes; The verification module includes: a first verification module, which is used for the first node to receive a first request from the second node, the first request is used to request verification whether to allow uploading of sensor data of the second node; the first node determines a first verification result according to the identification information of the sensor data corresponding to the second node, the first verification result is used to indicate that uploading of the sensor data corresponding to the second node is allowed, or the first verification result is used to indicate that uploading of the sensor data corresponding to the second node is not allowed, and the identification information of the sensor data corresponding to the second node comes from a node information identification neural network model that is trained on the cloud server and then sent to the edge device; the first node sends the first verification result to the second node; wherein the first node and the second node are adjacent nodes; A first judgment module, configured to determine that the second node is a valid node if the first verification result is that uploading of the sensor data corresponding to the second node is allowed; and to determine that the second node is an invalid node if the first verification result is that uploading of the sensor data corresponding to the second node is not allowed; A second verification module is used for a first node to receive a first request from a third node, the first request is used to request verification whether to allow uploading of sensor data of the third node, and the first node and the third node are both industrial sensor data; the first node determines a second verification result based on the identification information of the sensor data corresponding to the third node, the second verification result is used to indicate that uploading of the sensor data corresponding to the third node is allowed, or the second verification result is used to indicate that uploading of the sensor data corresponding to the third node is not allowed, and the identification information of the sensor data corresponding to the third node comes from a node information identification neural network model that is trained on the cloud server and then sent to the edge device; the first node sends the second verification result to the third node; wherein the first node and the third node are non-adjacent nodes; A second judgment module, configured to determine that the third node is a valid node if the second verification result is that uploading of the sensor data corresponding to the third node is allowed; and determine that the third node is an invalid node if the second verification result is that uploading of the sensor data corresponding to the third node is not allowed; A representative node determination module is used to determine a representative node from the valid nodes through a trained equivalence determination neural network model; wherein the representative node determination module is further used to group the valid nodes into a new sequence, and input the new sequence into the trained equivalence determination neural network model, group the valid nodes in the new sequence into equivalent groups, and select a valid node in each group as a representative node; The storage module is used to organize the representative nodes into a storage sequence and forward the storage sequence to the cloud server for storage.

4. A computer readable medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the industrial Internet platform data processing method as described in any one of claims 1 to 2 is implemented.

5. An electronic device, characterized in that: include: one or more processors; A storage device for storing one or more programs, which, when executed by the one or more processors, enables the one or more processors to implement the industrial Internet platform data processing method as described in any one of claims 1 to 2.

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