CN114996233A - Industrial Internet platform data processing method and device and computer readable medium - Google Patents

Abstract

The embodiment of the application provides an industrial internet platform data processing method and device, a computer readable medium and electronic equipment. According to the embodiment of the application, the data of the industrial sensor to be subjected to data filtering processing is obtained firstly; then configuring a sequence corresponding to the industrial sensor data into a plurality of nodes, so that verification is performed among the nodes, according to a preset verification mode, taking the node which is not verified as an invalid node, and taking the node which is verified as an valid node; forming a new sequence by the effective nodes, inputting the new sequence into a trained equivalence judgment neural network model, equivalently grouping the effective nodes in the new sequence, and selecting one effective node in each group as a representative node; and finally, forming a storage sequence by the representative nodes, and forwarding the storage sequence to a cloud server for storage, so that the data processing efficiency is improved, and the storage space pressure of the cloud server is reduced.

Description

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

This application is a divisional application of an invention application with an application date of February 21, 2022, a Chinese application number of 202210155523.8, and an invention title of "Industrial Internet Platform Data Processing Method, Device and Electronic Equipment".

technical field

The present application relates to the field of computer technology, and in particular, to a data processing method, apparatus, computer-readable medium, and electronic device for an industrial Internet platform.

Background technique

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 through edge devices for unified storage.

In the traditional industrial Internet, when performing data filtering processing, a certain device in the office network obtains all industrial real-time data from the real-time database, and performs data filtering processing based on all industrial real-time data. However, taking an industrial system of a certain scale as an example, there are about 100,000 sensors, and the daily output of industrial real-time data can reach hundreds of GB. If a certain device in the office network performs data filtering based on all industrial real-time data, it will The data processing efficiency is low.

SUMMARY OF THE INVENTION

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

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

According to an aspect of the embodiments of the present application, a data processing method for an industrial Internet platform is provided, which is applied to edge devices in the industrial Internet, and the method includes:

Obtain industrial sensor data to be processed by data filtering;

The sequence corresponding to the industrial sensor data is configured as a plurality of nodes, so that the nodes are verified, and according to a preset verification method, the nodes whose verification is not established are regarded as invalid nodes, and the nodes whose verification is established are regarded as valid nodes;

Determine the representative node from the valid nodes by using the trained equivalent judgment neural network model;

The representative nodes are formed into a storage sequence, and the storage sequence is forwarded to a cloud server for storage.

In some embodiments of the present application, based on the foregoing solution, determining the representative node from the valid nodes by using the trained equivalence decision neural network model includes: forming a new sequence of the valid nodes, and combining the new valid nodes into a new sequence. The sequence is input into the trained equivalence judgment neural network model, the valid nodes in the new sequence are grouped equally, and one valid node is selected as a representative node in each group.

In some embodiments of the present application, based on the aforementioned solution, the sequence corresponding to the industrial sensor data is configured as several nodes, so that verification is performed between nodes, and according to a preset verification method, the node that does not hold the verification is used as the node. Invalid nodes, the nodes that are verified as valid nodes, including:

The first node receives a first request from the second node, where the first request is used to request to verify whether the uploading of sensor data of the second node is allowed, and the first node and the second node are both industrial sensor data; The first node determines a first verification result according to the identification information of the sensor data corresponding to the second node, and the first verification result is used to indicate that the sensor data corresponding to the second node is allowed to be uploaded, or the first verification result is A verification result is used to indicate that the 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 the node information identification neural network that is trained on the cloud server and then sent to the edge device model; 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 the uploading of 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 the uploading of the sensor data corresponding to the second node is not allowed, Then it is determined that the second node is an invalid node;

The first node receives a first request from the third node, and the first request is used for requesting to verify whether the sensor data of the third node is allowed to be uploaded, and the first node and the third node are both industrial sensor data; The first node determines a second verification result according to the identification information of the sensor data corresponding to the third node, and the second verification result is used to indicate that the sensor data corresponding to the third node is allowed to be uploaded, or the third node The second verification result is used to indicate that the 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 the node information identification neural network that is trained on the cloud server and then sent to the edge device model; 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 the uploading of 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 the uploading of the sensor data corresponding to the third node is not allowed, then it is determined that the third node is an invalid node; and,

The second node receives a first request from the first node, where the first request is used to request to verify whether uploading the 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 according to the identification information of the sensor data corresponding to the second node, and the first verification result is used to indicate that the sensor data corresponding to the first node is allowed to be uploaded, or the first verification result is A verification result is used to indicate that the 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 the node information identification neural network that is trained on the cloud server and then sent to the edge device model; the second node sends the first verification result to the first node; wherein the first node and the second node are adjacent nodes;

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

The third node receives a first request from the first node, and the first request is used for requesting to verify whether uploading the 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 according to the identification information of the sensor data corresponding to the first node, and the second verification result is used to indicate that the sensor data corresponding to the first node is allowed to be uploaded, or the first node The second verification result is used to indicate that the 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 the node information identification neural network that is trained on the cloud server and then sent to the edge device model; the first node sends the second verification result to the first node; wherein the first node and the third node are non-adjacent nodes;

If the second verification result is that the uploading of 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 the uploading of the sensor data corresponding to the third node is not allowed, Then it is determined that the third node is an invalid node.

In some embodiments of the present application, based on the foregoing solution, the effective nodes are formed into a new sequence, and the new sequence is input into the trained equivalence decision neural network model, and the effective nodes in the new sequence are Equivalent grouping, select at least one valid node as the representative node in each group, including:

Input the new sequence composed of valid nodes into the trained equivalent decision neural network model;

The equivalent judgment neural network model judges valid nodes based on a preset dimension, and can use one or two valid nodes representing nodes as a valid node group; the preset dimension includes the value of the sensor data, and the previous Sensor bias, and absolute value of non-adjacent sensor bias and probability of occurrence:

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

According to an aspect of the embodiments of the present application, an industrial Internet platform data processing device is provided, including:

The acquisition module is used to acquire the industrial sensor data to be processed by data filtering;

The verification module is used to configure the sequence corresponding to the industrial sensor data into several nodes, so that verification is performed between nodes, and according to a preset verification method, the nodes that fail to be verified are regarded as invalid nodes, and the nodes that have been verified are regarded as valid nodes. ;

a representative node determination module, used for determining a representative node from the valid nodes through the trained equivalent judgment neural network model;

A storage module, configured to form a storage sequence of the representative nodes, and forward the storage sequence to a cloud server for storage.

In some embodiments of the present application, based on the foregoing solution, the verification module includes:

a first verification module, used for the first node to receive a first request from the second node, the first request being used for requesting to verify whether uploading the sensor data of the second node is allowed, the first node and the second node are industrial sensor data; the first node determines a first verification result according to the identification information of the sensor data corresponding to the second node, and the first verification result is used to indicate that the sensor corresponding to the second node is allowed to be uploaded data, or the first verification result is used to indicate that the 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 the training completed on the cloud server and then sent to the edge The node information of the device identifies the neural network model; the first node sends the first verification result to the second node; wherein the first node and the second node are adjacent nodes;

The first judgment module is configured to judge that the second node is a valid node if the first verification result is that the uploading of the sensor data corresponding to the second node is allowed; if the first verification result is that the uploading of the second node is not allowed For the sensor data corresponding to the second node, it is determined that the second node is an invalid node;

The second verification module is used for the first node to receive a first request from the third node, where the first request is used to request verification whether to allow uploading of sensor data of the third node, the first node and the third node are industrial sensor data; the first node determines a second verification result according to the identification information of the sensor data corresponding to the third node, and the second verification result is used to indicate that the sensor corresponding to the third node is allowed to be uploaded data, or the second verification result is used to indicate that the 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 the training completed on the cloud server and then sent to the edge The node information of the device identifies the neural network model; the first node sends the second verification result to the third node; wherein the first node and the third node are non-adjacent nodes;

The second judgment module is configured to judge that the third node is a valid node if the second verification result is that the uploading of the sensor data corresponding to the third node is allowed; if the second verification result is that the uploading of the third node is not allowed For the sensor data corresponding to the three nodes, it is determined that the third node is an invalid node;

The third verification module is used for the second node to receive a first request from the first node, where the first request is used for requesting to verify whether uploading the sensor data of the first node is allowed, the first node and the second node are industrial sensor data; the first node determines a first verification result according to the identification information of the sensor data corresponding to the second node, and the first verification result is used to indicate that the sensor corresponding to the first node is allowed to be uploaded data, or the first verification result is used to indicate that the 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 the training completed on the cloud server and then sent to the edge The node information of the device identifies the neural network model; the second node sends the first verification result to the first node; wherein the first node and the second node are adjacent nodes;

A third judging module, configured to judge that the second node is an invalid node if the first verification result is that the uploading of the sensor data corresponding to the second node is not allowed; if the first verification result is that the uploading of the second node is allowed For sensor data corresponding to a node, the first node sends a request to the third node;

a fourth verification module, used for the third node to receive a first request from the first node, where the first request is used to request to verify whether the sensor data of the first node is allowed to be uploaded, the first node and the third node are industrial sensor data; the third node determines a second verification result according to the identification information of the sensor data corresponding to the first node, and the second verification result is used to indicate that the sensor corresponding to the first node is allowed to be uploaded data, or the second verification result is used to indicate that the 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 the training completed on the cloud server and then sent to the edge The node information of the device identifies the neural network model; the first node sends the second verification result to the first node; wherein the first node and the third node are non-adjacent nodes;

The fourth judgment module is configured to judge that the third node is a valid node if the second verification result is that the uploading of the sensor data corresponding to the third node is allowed; if the second verification result is that the uploading of the third node is not allowed For the sensor data corresponding to the three nodes, it is determined that the third node is an invalid node.

According to an aspect of the embodiments of the present application, there is provided a computer-readable medium on which a computer program is stored, wherein the computer program implements the following method when executed by a processor:

Obtain industrial sensor data to be processed by data filtering;

The sequence corresponding to the industrial sensor data is configured as a plurality of nodes, so that the nodes are verified, and according to a preset verification method, the nodes whose verification is not established are regarded as invalid nodes, and the nodes whose verification is established are regarded as valid nodes;

Determine the representative node from the valid nodes by using the trained equivalent judgment neural network model;

The representative nodes are formed into a storage sequence, and the storage sequence is forwarded to a cloud server for storage.

According to an aspect of the embodiments of the present application, an electronic device is provided, characterized in that it includes:

one or more processors;

A storage device for storing one or more programs, when the one or more programs are executed by the one or more processors, the one or more processors implement the following methods:

Obtain industrial sensor data to be processed by data filtering;

The sequence corresponding to the industrial sensor data is configured as a plurality of nodes, so that the nodes are verified, and according to a preset verification method, the nodes whose verification is not established are regarded as invalid nodes, and the nodes whose verification is established are regarded as valid nodes;

Determine the representative node from the valid nodes by using the trained equivalent judgment neural network model;

The representative nodes are formed into a storage sequence, and the storage sequence is forwarded to a cloud server for storage.

In the technical solutions provided by some embodiments of the present application, by first acquiring the industrial sensor data to be subjected to data filtering processing; According to the preset verification method, the nodes that fail to be verified are regarded as invalid nodes, and the nodes that are established are regarded as valid nodes; the representative nodes are determined from the valid nodes through the trained equivalent judgment neural network model; finally, the representative nodes are A storage sequence is formed, and the storage sequence is forwarded to the cloud server for storage, which improves the data processing efficiency and reduces the storage space pressure of the cloud server.

It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not limiting of the present application.

Description of drawings

The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the application and together with the description serve to explain the principles of the application. Obviously, the drawings in the following description are only some embodiments of the present application, and for those of ordinary skill in the art, other drawings can also be obtained from these drawings without creative effort.

1 shows a schematic flowchart of a data processing method for an industrial Internet platform to which the technical solutions of the embodiments of the present application can be applied;

FIG. 2 schematically shows a schematic diagram of an industrial Internet platform data processing apparatus according to an embodiment of the present application;

FIG. 3 schematically shows a schematic diagram of a verification module according to an embodiment of the present application;

FIG. 4 schematically shows another schematic diagram of a verification module according to an embodiment of the present application;

FIG. 5 schematically shows yet another schematic diagram of a verification module according to an embodiment of the present application;

FIG. 6 shows a schematic structural diagram of a computer system suitable for implementing the electronic device according to the embodiment of the present application.

Detailed ways

Example embodiments will now be described more fully with reference to the accompanying drawings. Example embodiments, however, can be embodied in various 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 thorough and complete, and will fully convey the concept of example embodiments to those skilled in the art.

Furthermore, the described features, structures, or characteristics may be combined in any suitable manner in one or more embodiments. In the following description, numerous specific details are provided in order to give a thorough understanding of the embodiments of the present application. However, those skilled in the art will appreciate that the technical solutions of the present application may be practiced without one or more of the specific details, or other methods, components, devices, steps, etc. may be employed. In other instances, well-known methods, devices, implementations, or operations have not been shown or described in detail to avoid obscuring aspects of the present application.

The block diagrams shown in the figures are merely functional entities and do not necessarily necessarily correspond to physically separate entities. That is, these functional entities may be implemented in software, or in one or more hardware modules or integrated circuits, or in different networks and/or processor devices and/or microcontroller devices entity.

The flowcharts shown in the figures are only exemplary illustrations and do not necessarily include all contents and operations/steps, nor do they have to be performed 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 be changed according to the actual situation.

As some embodiments of the present invention, FIG. 1 shows a schematic flowchart of a method for processing data on an industrial Internet platform. The industrial internet platform data processing method is applied to edge devices in the industrial internet, and the method includes:

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

The industrial sensor data includes data of various sensors, wherein 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, a "sensor channel" can be defined. Specifically, one sensor channel is used to collect one physical signal, and the system assigns a unique ID to each sensor channel. When the sensor data needs to be acquired, the function interface for acquiring the sensor data can be called in the application program.

S102: Configure the sequence corresponding to the industrial sensor data as several nodes, so that verification is performed between nodes, and according to a preset verification method, a node that fails to be verified is regarded as an invalid node, and a node that is verified is regarded as a valid node.

S103: Form the valid nodes into a new sequence, input the new sequence into the trained equivalence judgment neural network model, group the valid nodes in the new sequence into equal groups, and select an valid node in each group as a representative node.

For S102 and S103, the purpose is to find out the valid and representative sensor data of the representative node.

S104: Form the representative node into a storage sequence, and forward the storage sequence to a cloud server for storage.

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

In the technical solutions provided by some embodiments of the present application, by first acquiring the industrial sensor data to be subjected to data filtering processing; According to the preset verification method, the nodes that fail to be verified are regarded as invalid nodes, and the nodes that are established are regarded as valid nodes; the valid nodes are formed into a new sequence, and the new sequence is input into the trained equivalent judgment neural network model, and the The valid nodes in the new sequence are grouped into equal groups, and one 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, which improves data efficiency. The processing efficiency is improved, and the storage space pressure of the cloud server is also reduced.

In some embodiments of the present application, based on the foregoing solution, S102 specifically includes:

S201: The first node receives a first request from the second node, where the first request is used to request to verify whether the 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 according to the identification information of the sensor data corresponding to the second node, and the first verification result is used to indicate that the sensor data corresponding to the second node is allowed to be uploaded, or the The first verification result is used to indicate that the 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 the identification of the node information after the training is completed on the cloud server and then sent to the edge device. A neural network model; the first node sends the first verification result to the second node; wherein the first node and the second node are adjacent nodes;

S202: If the first verification result is that uploading the sensor data corresponding to the second node is allowed, determine that the second node is a valid node; if the first verification result is that the uploading of the sensor corresponding to the second node is not allowed data, then it is determined that the second node is an invalid node;

S203: The first node receives a first request from the third node, where the first request is used to request to verify whether the uploading of sensor data of the third node is allowed, and both the first node and the third node are industrial sensor data ; The first node determines a second verification result according to the identification information of the sensor data corresponding to the third node, and the second verification result is used to indicate that the sensor data corresponding to the third node is allowed to be uploaded, or, the The second verification result is used to indicate that the 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 the identification of the node information after the training is completed on the cloud server and then sent to the edge device. A neural network model; the first node sends the second verification result to the third node; wherein the first node and the third node are non-adjacent nodes;

S204: If the second verification result is that uploading the sensor data corresponding to the third node is allowed, determine that the third node is a valid node; if the second verification result is that the uploading of the sensor corresponding to the third node is not allowed data, it is determined that the third node is an invalid node.

In some embodiments of the present application, based on the foregoing solution, S102 specifically includes:

S301: The second node receives a first request from the first node, where the first request is used to request to verify whether to allow uploading of sensor data of the first node, the first node and the second node are both industrial sensor data ; the first node determines a first verification result according to the identification information of the sensor data corresponding to the second node, and the first verification result is used to indicate that the sensor data corresponding to the first node is allowed to be uploaded, or, the The first verification result is used to indicate that the 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 the identification of the node information after the training is completed on the cloud server and then sent to the edge device. A neural network model; the second node sends the first verification result to the first node; wherein the first node and the second node are adjacent nodes.

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

S303: The third node receives a first request from the first node, where the first request is used for requesting to verify whether uploading the sensor data of the first node is allowed, and both the first node and the third node are industrial sensor data ; The third node determines a second verification result according to the identification information of the sensor data corresponding to the first node, and the second verification result is used to indicate that the sensor data corresponding to the first node is allowed to be uploaded, or, the The second verification result is used to indicate that the 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 the identification of the node information after the training is completed on the cloud server and then sent to the edge device. A neural network model; the first node sends the second verification result to the first node; wherein the first node and the third node are non-adjacent nodes.

S304: If the second verification result is that uploading the sensor data corresponding to the third node is allowed, determine that the third node is a valid node; if the second verification result is that the uploading of the sensor corresponding to the third node is not allowed data, it is determined that the third node is an invalid node.

As some embodiments of the present application, based on the foregoing solution, S102 specifically includes:

S401: The first node receives a first request from the second node, where the first request is used for requesting to verify whether the 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 according to the identification information of the sensor data corresponding to the second node, and the first verification result is used to indicate that the sensor data corresponding to the second node is allowed to be uploaded, or the The first verification result is used to indicate that the 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 the identification of the node information after the training is completed on the cloud server and then sent to the edge device. A neural network model; the first node sends the first verification result to the second node; wherein the first node and the second node are adjacent nodes.

S402: If the first verification result is that uploading the sensor data corresponding to the second node is allowed, determine that the second node is a valid node; if the first verification result is that the uploading of the sensor corresponding to the second node is not allowed data, it is determined that the second node is an invalid node.

S403: The first node receives a first request from the third node, where the first request is used to request to verify whether the uploading of sensor data of the third node is allowed, and both the first node and the third node are industrial sensor data ; The first node determines a second verification result according to the identification information of the sensor data corresponding to the third node, and the second verification result is used to indicate that the sensor data corresponding to the third node is allowed to be uploaded, or, the The second verification result is used to indicate that the 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 the identification of the node information after the training is completed on the cloud server and then sent to the edge device. A neural network model; the first node sends the second verification result to the third node; wherein the first node and the third node are non-adjacent nodes.

S404: If the second verification result is that uploading the sensor data corresponding to the third node is allowed, determine that the third node is a valid node; if the second verification result is that the uploading of the sensor corresponding to the third node is not allowed data, it is determined that the third node is an invalid node.

S405: The second node receives a first request from the first node, where the first request is used to request to verify whether uploading the sensor data of the first node is allowed, and both the first node and the second node are industrial sensor data ; the first node determines a first verification result according to the identification information of the sensor data corresponding to the second node, and the first verification result is used to indicate that the sensor data corresponding to the first node is allowed to be uploaded, or, the The first verification result is used to indicate that the 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 the identification of the node information after the training is completed on the cloud server and then sent to the edge device. A neural network model; the second node sends the first verification result to the first node; wherein the first node and the second node are adjacent nodes.

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

S407: The third node receives a first request from the first node, where the first request is used for requesting to verify whether uploading sensor data of the first node is allowed, and both the first node and the third node are industrial sensor data ; The third node determines a second verification result according to the identification information of the sensor data corresponding to the first node, and the second verification result is used to indicate that the sensor data corresponding to the first node is allowed to be uploaded, or, the The second verification result is used to indicate that the 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 the identification of the node information after the training is completed on the cloud server and then sent to the edge device. A neural network model; the first node sends the second verification result to the first node; wherein the first node and the third node are non-adjacent nodes.

S408: If the second verification result is that uploading the sensor data corresponding to the third node is allowed, determine that the third node is a valid node; if the second verification result is that the uploading of the sensor corresponding to the third node is not allowed data, it is determined that the third node is an invalid node.

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 validation. For verification and calculation, the computational efficiency is not reduced.

In some embodiments of the present application, based on the foregoing solution, S103 specifically includes:

S501: Input a new sequence composed of valid nodes into the trained equivalence judgment neural network model.

S502: The equivalent judgment neural network model judges valid nodes based on a preset dimension, and uses one or two valid nodes representing nodes as a valid node group; the preset dimension includes the value of the sensor data, and the previous A sensor bias, and the absolute value of the non-adjacent sensor bias and the probability of that value occurring.

S503: Group the valid nodes based on the valid node group to obtain multiple equivalent groups; and determine the representative node of each equivalent group.

In some embodiments of the present application, based on the foregoing solution, S102 specifically includes:

S601: Calculate the probability that the current node is an effective node by the following formula;

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 preset weights respectively, and W _{xl_n} +W _{fxl_n} =1, 1≤n≤N, and N is the total number of sensor nodes.

S602: If the probability that the current node is an effective node is greater than a preset threshold, determine that the current node verification is established; if the probability that the current node is an effective node is less than or equal to a preset threshold, determine that the current node verification is not established.

S603: The node whose verification fails to be established is regarded as an invalid node, and the node whose verification is established is regarded as a valid node.

As some embodiments of the present application, as shown in FIG. 2 , an industrial Internet platform data processing apparatus 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 .

Wherein, the acquisition module 11 is used to acquire the industrial sensor data to be processed by data filtering; the verification module 12 is used to configure the sequence corresponding to the industrial sensor data into several nodes, so that the verification between the nodes is performed according to the preset In the verification method, the nodes that are not verified are regarded as invalid nodes, and the nodes that are verified are regarded as valid nodes; the representative node determination module 13 is used to form a new sequence of the valid nodes, and input the new sequence into the trained equivalent judgment. Neural network model, the valid nodes in the new sequence are equally grouped, and one valid node is selected as a representative node in each group; the storage module 14 is used to form a storage sequence of the representative nodes, and forward the storage sequence to the cloud server for storage.

As some embodiments of the present application, as shown in FIG. 3 , a schematic diagram of the verification module 12 is provided. The verification module 12 includes a first verification module 121 , a first determination module 122 , a second verification module 123 and a second determination module 124 .

Wherein, the first verification module 121 is used for the first node to receive a first request from the second node, where the first request is used for requesting to verify whether the uploading of sensor data of the second node is allowed, the first node and the The second nodes are all industrial sensor data; the first node determines a first verification result according to 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 second node is allowed The corresponding sensor data, or the first verification result is used to indicate that the 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 The node information sent to the edge device identifies the neural network model; the first node sends the first verification result to the second node; wherein the first node and the second node are adjacent nodes.

The first judgment module 122 is configured to judge that the second node is a valid node if the first verification result is that the uploading of the sensor data corresponding to the second node is allowed; if the first verification result is that the uploading of the second node is not allowed For the sensor data corresponding to the second node, it is determined that the second node is an invalid node.

The second verification module 123 is configured for the first node to receive a first request from a third node, where the first request is used to request verification whether to allow uploading of sensor data of the third node, the first node and the third node The nodes are all industrial sensor data; the first node determines a second verification result according to the identification information of the sensor data corresponding to the third node, and the second verification result is used to indicate that the uploading of the corresponding data of the third node is allowed. The sensor data, or the second verification result is used to indicate that the 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 the training completed on the cloud server and then sent to The node information of the edge device identifies the neural network model; the first node sends the second verification result to the third node; wherein the first node and the third node are non-adjacent nodes.

The second judgment module 124 is configured to judge that the third node is a valid node if the second verification result is that the uploading of the sensor data corresponding to the third node is allowed; if the second verification result is that the uploading of the sensor data is not allowed For the sensor data corresponding to the third node, it is determined that the third node is an invalid node.

As some embodiments of the present application, as shown in FIG. 4 , 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 .

The third verification module 125 is used for the second node to receive a first request from the first node, where the first request is used for requesting to verify whether uploading the sensor data of the first node is allowed, the first node and the second node The nodes are all industrial sensor data; the first node determines a first verification result according to the identification information of the sensor data corresponding to the second node, and the first verification result is used to indicate that the uploading of the corresponding data of the first node is allowed. sensor data, or the first verification result is used to indicate that the 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 the training completed on the cloud server and then sent to The node information of the edge device identifies the neural network model; the second node sends the first verification result to the first node; wherein the first node and the second node are adjacent nodes.

The third judging module 126 is configured to judge that the second node is an invalid node if the first verification result is that the uploading of the sensor data corresponding to the second node is not allowed; if the first verification result is that the uploading of the second node is allowed the sensor data corresponding to the first node, the first node sends a request to the third node.

The fourth verification module 127 is used for the third node to receive a first request from the first node, where the first request is used to request verification whether to allow uploading of sensor data of the first node, the first node and the third The nodes are all industrial sensor data; the third node determines a second verification result according to the identification information of the sensor data corresponding to the first node, and the second verification result is used to indicate that the uploading of the corresponding data of the first node is allowed. sensor data, or the second verification result is used to indicate that the 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 the training completed on the cloud server and then sent to The node information of the edge device identifies the neural network model; the first node sends the second verification result to the first node; wherein the first node and the third node are non-adjacent nodes.

The fourth determination module 128 is configured to determine that the third node is a valid node if the second verification result is that the sensor data corresponding to the third node is allowed to be uploaded; if the second verification result is that the uploading of the third node is not allowed For the sensor data corresponding to the third node, it is determined that the third node is an invalid node.

As some embodiments of the present application, as shown in FIG. 5 , a schematic diagram of the verification module 12 is provided. The verification module 12 includes a first verification module 121, a first determination module 122, a second verification module 123, a second determination module 124, a third verification module 125, a third determination module 126, a fourth verification module 127 and a fourth determination module 128.

Wherein, the first verification module 121 is used for the first node to receive a first request from the second node, where the first request is used for requesting to verify whether the uploading of sensor data of the second node is allowed, the first node and the The second nodes are all industrial sensor data; the first node determines a first verification result according to 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 second node is allowed The corresponding sensor data, or the first verification result is used to indicate that the 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 The node information sent to the edge device identifies the neural network model; the first node sends the first verification result to the second node; wherein the first node and the second node are adjacent nodes;

The first judgment module 122 is configured to judge that the second node is a valid node if the first verification result is that the uploading of the sensor data corresponding to the second node is allowed; if the first verification result is that the uploading of the second node is not allowed For the sensor data corresponding to the second node, it is determined that the second node is an invalid node;

The second verification module 123 is configured for the first node to receive a first request from a third node, where the first request is used to request verification whether to allow uploading of sensor data of the third node, the first node and the third node The nodes are all industrial sensor data; the first node determines a second verification result according to the identification information of the sensor data corresponding to the third node, and the second verification result is used to indicate that the uploading of the corresponding data of the third node is allowed. The sensor data, or the second verification result is used to indicate that the 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 the training completed on the cloud server and then sent to The node information of the edge device identifies the neural network model; the first node sends the second verification result to the third node; wherein the first node and the third node are non-adjacent nodes;

The second judgment module 124 is configured to judge that the third node is a valid node if the second verification result is that the uploading of the sensor data corresponding to the third node is allowed; if the second verification result is that the uploading of the sensor data is not allowed For the sensor data corresponding to the third node, it is determined that the third node is an invalid node.

The third verification module 125 is used for the second node to receive a first request from the first node, where the first request is used for requesting to verify whether uploading the sensor data of the first node is allowed, the first node and the second node The nodes are all industrial sensor data; the first node determines a first verification result according to the identification information of the sensor data corresponding to the second node, and the first verification result is used to indicate that the uploading of the corresponding data of the first node is allowed. sensor data, or the first verification result is used to indicate that the 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 the training completed on the cloud server and then sent to The node information of the edge device identifies the neural network model; the second node sends the first verification result to the first node; wherein the first node and the second node are adjacent nodes;

The third judging module 126 is configured to judge that the second node is an invalid node if the first verification result is that the uploading of the sensor data corresponding to the second node is not allowed; if the first verification result is that the uploading of the second node is allowed the sensor data corresponding to the first node, the first node sends a request to the third node;

The fourth verification module 127 is used for the third node to receive a first request from the first node, where the first request is used to request verification whether to allow uploading of sensor data of the first node, the first node and the third The nodes are all industrial sensor data; the third node determines a second verification result according to the identification information of the sensor data corresponding to the first node, and the second verification result is used to indicate that the uploading of the corresponding data of the first node is allowed. sensor data, or the second verification result is used to indicate that the 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 the training completed on the cloud server and then sent to The node information of the edge device identifies the neural network model; the first node sends the second verification result to the first node; wherein the first node and the third node are non-adjacent nodes;

The fourth determination module 128 is configured to determine that the third node is a valid node if the second verification result is that the sensor data corresponding to the third node is allowed to be uploaded; if the second verification result is that the uploading of the third node is not allowed For the sensor data corresponding to the third node, it is determined that the third node is an invalid node.

According to an aspect of the embodiments of the present application, there is provided a computer-readable medium on which a computer program is stored, wherein the computer program implements the following method when executed by a processor:

Obtain industrial sensor data to be processed by data filtering;

The sequence corresponding to the industrial sensor data is configured as a plurality of nodes, so that the nodes are verified, and according to a preset verification method, the nodes whose verification is not established are regarded as invalid nodes, and the nodes whose verification is established are regarded as valid nodes;

The effective nodes are formed into a new sequence, and the new sequence is input into the trained equivalent judgment neural network model, the effective nodes in the new sequence are equally grouped, and an effective node is selected as a representative node in each group;

The representative nodes are formed into a storage sequence, and the storage sequence is forwarded to a cloud server for storage.

According to an aspect of the embodiments of the present application, an electronic device is provided, characterized in that it includes:

one or more processors;

A storage device for storing one or more programs, when the one or more programs are executed by the one or more processors, the one or more processors implement the following methods:

Obtain industrial sensor data to be processed by data filtering;

The sequence corresponding to the industrial sensor data is configured as a plurality of nodes, so that the nodes are verified, and according to a preset verification method, the nodes whose verification is not established are regarded as invalid nodes, and the nodes whose verification is established are regarded as valid nodes;

The effective nodes are formed into a new sequence, and the new sequence is input into the trained equivalent judgment neural network model, the effective nodes in the new sequence are equally grouped, and an effective node is selected as a representative node in each group;

The representative nodes are formed into a storage sequence, and the storage sequence is forwarded to a cloud server for storage.

FIG. 6 shows a schematic structural diagram of a computer system suitable for implementing the electronic device according to the embodiment of the present application.

It should be noted that the computer system 600 of the electronic device shown in FIG. 6 is only an example, and should not impose any limitations on the functions and scope of use of the embodiments of the present application.

As shown in FIG. 6 , the computer system 600 includes a central processing unit (Central Processing Unit, CPU) 601, which can be loaded into a random device according to a program stored in a read-only memory (Read-Only Memory, ROM) 602 or from a storage part 608 A program in a memory (Random Access Memory, RAM) 603 is accessed to perform various appropriate actions and processes, for example, the methods described in the above embodiments are performed. In the RAM 603, various programs and data necessary for system operation are also stored. The CPU 601 , the ROM 602 , and the RAM 603 are connected to each other through a bus 606 . An Input/Output (I/O) interface 606 is also connected to the bus 606 .

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 part 608 including a hard disk and the like; and a communication part 609 including a network interface card such as a LAN (Local Area Network) card, a modem, and the like. The communication section 609 performs communication processing via a network such as the Internet. Drivers 610 are also connected to 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 mounted on the drive 610 as needed so that a computer program read therefrom is installed into the storage section 608 as needed.

In particular, according to embodiments of the present application, the processes described above with reference to the flowcharts may be implemented as computer software programs. For example, embodiments of the present application include a computer program product comprising a computer program carried on a computer-readable medium, the computer program comprising a computer program for performing the method illustrated in the flowchart. In such an embodiment, the computer program may be downloaded and installed from the network via the communication portion 609 and/or installed from the removable medium 611 . When the computer program is executed by the central processing unit (CPU) 601, various functions defined in the system of the present application are executed.

It should be noted that the computer-readable medium shown in the embodiments 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 can be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus or device, or a combination of any of the above. More specific examples of computer readable storage media may include, but are not limited to, electrical connections with one or more wires, portable computer disks, hard disks, random access memory (RAM), read only memory (ROM), erasable Erasable Programmable Read Only Memory (EPROM), flash memory, optical fiber, portable Compact Disc Read-Only Memory (CD-ROM), optical storage device, magnetic storage device, or any suitable of the above The combination. In this application, a computer-readable storage medium can be any tangible medium that contains or stores a program that can be used by or in conjunction with an instruction execution system, apparatus, or device. In this application, however, a computer-readable signal medium may include a data signal propagated in baseband or as part of a carrier wave, carrying a computer-readable computer program therein. 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 foregoing. A computer-readable signal medium can also be any computer-readable medium other than a computer-readable storage medium that can transmit, propagate, or transport the program for use by or in connection with the instruction execution system, apparatus, or device . A computer program embodied on a computer-readable medium may be transmitted using any suitable medium, including but not limited to: wireless, wired, etc., or any suitable combination of the foregoing.

The flowchart and block diagrams in the Figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present application. Wherein, each block in the flowchart or block diagram may represent a module, program segment, or part of code, and the above-mentioned module, program segment, or part of code contains one or more executables for realizing the specified logical function instruction. It should also be noted that, in some alternative implementations, the functions noted in the blocks may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It is also noted that each block of the block diagrams or flowchart illustrations, and combinations of blocks in the block diagrams or flowchart illustrations, can be implemented in special purpose hardware-based systems that perform the specified functions or operations, or can be implemented using A combination of dedicated hardware and computer instructions is implemented.

The units involved in the embodiments of the present application may be implemented in software or hardware, and the described units may also be provided in a processor. Among them, the names of these units do not constitute a limitation on the unit itself under certain circumstances.

According to one aspect of the present application, there is provided a computer program product or computer program comprising computer instructions stored in a computer readable storage medium. The processor of the computer device reads the computer instructions from the computer-readable storage medium, and the processor executes the computer instructions to cause the computer device to perform the methods provided in the various optional implementations described above.

As another aspect, the present application also provides a computer-readable medium. The computer-readable medium may be included in the electronic device described in the above embodiments; it may also exist alone without being assembled into the electronic device. middle. The above-mentioned computer-readable medium carries one or more programs, and when the above-mentioned one or more programs are executed by an electronic device, enables the electronic device to implement the methods described in the above-mentioned embodiments.

It should be noted that although several modules or units of the apparatus for action performance are mentioned in the above detailed description, this division is not mandatory. Indeed, according to embodiments of the present application, the features and functions of two or more modules or units described above may be embodied in one module or unit. Conversely, the features and functions of one module or unit described above may be further divided into multiple modules or units to be embodied.

From the description of the above embodiments, those skilled in the art can easily understand that the exemplary embodiments described herein may be implemented by software, or may be implemented by software combined with necessary hardware. Therefore, the technical solutions according to the embodiments of the present application may be embodied in the form of software products, and the software products may be stored in a non-volatile storage medium (which may be CD-ROM, U disk, mobile hard disk, etc.) or on the network , which includes several instructions to cause a computing device (which may be a personal computer, a server, a touch terminal, or a network device, etc.) to execute the method according to the embodiments of the present application.

Other embodiments of the present application will readily occur to those skilled in the art upon consideration of the specification and practice of the embodiments disclosed herein. This application is intended to cover any variations, uses or adaptations of this application that follow the general principles of this application and include common knowledge or conventional techniques in the technical field not disclosed in this application .

It is to be understood that the present application is not limited to the precise structures described above and illustrated in the accompanying drawings and that various modifications and changes may be made without departing from the scope thereof. The scope of the application is limited only by the appended claims.

Claims (8)

1. An industrial internet platform data processing method is applied to an edge device in an industrial internet, and the method comprises the following steps:

acquiring industrial sensor data to be subjected to data filtering processing;

configuring the sequence corresponding to the industrial sensor data into a plurality of nodes, so that verification is performed among the nodes, according to a preset verification mode, taking the node which is not verified as an invalid node, and taking the node which is verified as an valid node;

determining representative nodes from the effective nodes through a trained equivalent decision neural network model;

and forming a storage sequence by the representative nodes, and forwarding the storage sequence to a cloud server for storage.

2. The industrial internet platform data processing method of claim 1, wherein the determining representative nodes from the valid nodes through the trained equivalence predicate neural network model comprises:

and forming a new sequence by the effective nodes, inputting the new sequence into a trained equivalence judgment neural network model, equivalently grouping the effective nodes in the new sequence, and selecting one effective node in each group as a representative node.

3. The industrial internet platform data processing method of claim 1, wherein the configuring the sequence corresponding to the industrial sensor data into a plurality of nodes to perform verification between the nodes, and according to a preset verification mode, regarding a node which is not verified as an invalid node and regarding a node which is verified as a valid node, comprises:

the method comprises the steps that a first node receives a first request from a second node, wherein the first request is used for requesting verification whether uploading of sensor data of the second node is allowed; the first node determines a first verification result according to the identification information of the sensor data corresponding to the second node, wherein the first verification result is used for indicating that the sensor data corresponding to the second node is allowed to be uploaded, or the first verification result is used for indicating that the sensor data corresponding to the second node is not allowed to be uploaded, and the identification information of the sensor data corresponding to the second node is from a node information identification neural network model which is trained at a cloud server end and then sent to edge equipment; 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 the sensor data corresponding to the second node is allowed to be uploaded, the second node is judged to be an effective node; if the first verification result is that the sensor data corresponding to the second node is not allowed to be uploaded, the second node is judged to be an invalid node;

a first node receives a first request from a third node, wherein the first request is used for requesting to verify whether sensor data of the third node is allowed to be uploaded or not, and the first node and the third node are industrial sensor data; the first node determines a second verification result according to the identification information of the sensor data corresponding to the third node, wherein the second verification result is used for indicating that the sensor data corresponding to the third node is allowed to be uploaded, or the second verification result is used for indicating that the sensor data corresponding to the third node is not allowed to be uploaded, and the identification information of the sensor data corresponding to the third node comes from a node information identification neural network model which is trained at a cloud server end and then sent to edge equipment; the first node sending 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 the sensor data corresponding to the third node is allowed to be uploaded, the third node is judged to be an effective node; if the second verification result is that the sensor data corresponding to the third node is not allowed to be uploaded, determining that the third node is an invalid node; and the combination of (a) and (b),

the second node receives a first request from the first node, wherein the first request is used for requesting verification whether the sensor data of the first node is allowed to be uploaded or not; the first node determines a first verification result according to the identification information of the sensor data corresponding to the second node, wherein the first verification result is used for indicating that the sensor data corresponding to the first node is allowed to be uploaded, or the first verification result is used for indicating that the sensor data corresponding to the first node is not allowed to be uploaded, and the identification information of the sensor data corresponding to the first node is from a node information identification neural network model which is trained at a cloud server end and then sent to edge equipment; the second node sends the first verification result to the first node; wherein the first node and the second node are adjacent nodes;

if the first verification result is that the sensor data corresponding to the second node is not allowed to be uploaded, the second node is judged to be an invalid node; if the first verification result is that the sensor data corresponding to the first node is allowed to be uploaded, the first node sends a request to a third node;

a third node receives a first request from a first node, wherein the first request is used for requesting to verify whether sensor data of the first node is allowed to be uploaded or not, and the first node and the third node are industrial sensor data; the third node determines a second verification result according to the identification information of the sensor data corresponding to the first node, wherein the second verification result is used for indicating that the sensor data corresponding to the first node is allowed to be uploaded, or the second verification result is used for indicating that the sensor data corresponding to the first node is not allowed to be uploaded, and the identification information of the sensor data corresponding to the first node is from a node information identification neural network model which is trained at a cloud server end and then sent to edge equipment; the first node sends the second verification result to the first node; wherein the first node and the third node are non-adjacent nodes;

if the second verification result is that the sensor data corresponding to the third node is allowed to be uploaded, the third node is judged to be a valid node; and if the second verification result is that the sensor data corresponding to the third node is not allowed to be uploaded, determining that the third node is an invalid node.

4. The industrial internet platform data processing method of claim 2, wherein the forming the effective nodes into a new sequence, inputting the new sequence into a trained equivalence judgment neural network model, and equivalently grouping the effective nodes in the new sequence, wherein selecting at least one effective node in each group as a representative node comprises:

inputting a new sequence formed by the effective nodes into a trained equivalent decision neural network model;

the equivalence judgment neural network model judges effective nodes based on preset dimensionality, and takes the effective nodes capable of using one or two representative nodes as effective node groups; the preset dimensionality comprises a numerical value of sensor data, deviation from a previous sensor, an absolute value of deviation of a non-adjacent sensor and probability of the numerical value;

grouping the effective nodes based on the effective node group to obtain a plurality of equivalent groups; and determines a representative node for each equivalent packet.

5. An industrial internet platform data processing apparatus, the apparatus comprising:

the acquisition module is used for acquiring industrial sensor data to be subjected to data filtering processing;

the verification module is used for configuring the sequence corresponding to the industrial sensor data into a plurality of nodes, so that verification is performed among the nodes, the nodes which are not verified are used as invalid nodes according to a preset verification mode, and the nodes which are verified are used as valid nodes;

the representative node determining module is used for determining representative nodes from the effective nodes through a trained equivalent decision neural network model;

and the storage module is used for forming a storage sequence by the representative nodes and forwarding the storage sequence to a cloud server for storage.

6. The industrial internet platform data processing device of claim 5, wherein the validation module comprises:

a first verification module, configured to receive, by a first node, a first request from a second node, where the first request is used to request verification whether uploading of sensor data of the second node is allowed; the first node determines a first verification result according to the identification information of the sensor data corresponding to the second node, wherein the first verification result is used for indicating that the sensor data corresponding to the second node is allowed to be uploaded, or the first verification result is used for indicating that the sensor data corresponding to the second node is not allowed to be uploaded, and the identification information of the sensor data corresponding to the second node is from a node information identification neural network model which is trained at a cloud server end and then sent to edge equipment; the first node sends the first verification result to the second node; the first node and the second node are adjacent nodes;

the first judgment module is used for judging that the second node is an effective node if the first verification result is that the sensor data corresponding to the second node is allowed to be uploaded; if the first verification result is that the sensor data corresponding to the second node is not allowed to be uploaded, the second node is judged to be an invalid node;

the second verification module is used for receiving a first request from a third node by a first node, the first request is used for requesting verification whether sensor data of the third node is allowed to be uploaded, and the first node and the third node are industrial sensor data; the first node determines a second verification result according to the identification information of the sensor data corresponding to the third node, wherein the second verification result is used for indicating that the sensor data corresponding to the third node is allowed to be uploaded, or the second verification result is used for indicating that the sensor data corresponding to the third node is not allowed to be uploaded, and the identification information of the sensor data corresponding to the third node comes from a node information identification neural network model which is trained at a cloud server end and then sent to edge equipment; the first node sending the second verification result to the third node; wherein the first node and the third node are non-adjacent nodes;

the second judgment module is used for judging that the third node is an effective node if the second verification result is that the sensor data corresponding to the third node is allowed to be uploaded; if the second verification result is that the sensor data corresponding to the third node is not allowed to be uploaded, determining that the third node is an invalid node;

a third verification module, configured to receive, by the second node, a first request from the first node, where the first request is used to request verification whether uploading of sensor data of the first node is allowed; the first node determines a first verification result according to the identification information of the sensor data corresponding to the second node, wherein the first verification result is used for indicating that the sensor data corresponding to the first node is allowed to be uploaded, or the first verification result is used for indicating that the sensor data corresponding to the first node is not allowed to be uploaded, and the identification information of the sensor data corresponding to the first node is from a node information identification neural network model which is trained at a cloud server end and then sent to edge equipment; the second node sends the first verification result to the first node; wherein the first node and the second node are adjacent nodes;

the third judging module is used for judging that the second node is an invalid node if the first verification result is that the sensor data corresponding to the second node is not allowed to be uploaded; if the first verification result is that the sensor data corresponding to the first node is allowed to be uploaded, the first node sends a request to a third node;

the fourth verification module is used for receiving a first request from the first node by the third node, the first request is used for requesting verification whether the sensor data of the first node is allowed to be uploaded, and the first node and the third node are industrial sensor data; the third node determines a second verification result according to the identification information of the sensor data corresponding to the first node, wherein the second verification result is used for indicating that the sensor data corresponding to the first node is allowed to be uploaded, or the second verification result is used for indicating that the sensor data corresponding to the first node is not allowed to be uploaded, and the identification information of the sensor data corresponding to the first node is from a node information identification neural network model which is trained at a cloud server end and then sent to edge equipment; the first node sends the second verification result to the first node; wherein the first node and the third node are non-adjacent nodes;

the fourth judging module is used for judging that the third node is an effective node if the second verification result is that the sensor data corresponding to the third node is allowed to be uploaded; and if the second verification result is that the sensor data corresponding to the third node is not allowed to be uploaded, determining that the third node is an invalid node.

7. A computer-readable medium, on which a computer program is stored, which, when being executed by a processor, implements the industrial internet platform data processing method according to any one of claims 1 to 4.

8. An electronic device, comprising:

one or more processors;

a storage device to store one or more programs that, when executed by the one or more processors, cause the one or more processors to implement the industrial internet platform data processing method of any one of claims 1 to 4.

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