CN115633090B - Multi-source data linking method based on eSIM card and 5G network - Google Patents
Multi-source data linking method based on eSIM card and 5G network Download PDFInfo
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Abstract
The invention discloses a multisource data linking method based on an eSIM card and a 5G network, which comprises the following steps: monitoring multi-source data such as videos, images, characters, instructions and the like acquired by power grid asset equipment, and preprocessing the multi-source data; transmitting the preprocessed multi-source data based on the communication capability of the 5G base station; and carrying out data link on the multi-source data to obtain a data chain. According to the invention, the computation speed of the data link process is improved by preprocessing the multi-source data, the data transmission rate is improved by the 5G power Internet of things monitoring and construction platform, the real-time data transmission is realized, the correlation is distinguished by adopting different methods for the data of different character types, meanwhile, a parallel computing data link mode is provided, the generation time of a data link can be greatly saved under the condition of complex data information types, and the data information processing efficiency is improved.
Description
Technical Field
The invention belongs to the technical field of monitoring and data processing of the electric power Internet of things, and particularly relates to a multisource data linking method based on an eSIM card and a 5G network.
Background
At present, the electric power Internet of things is taken as an Internet of things architecture, is in a concrete expression form and application floor of the electric power industry, and is a transition form for the electric power industry to develop innovation to the energy Internet. In the construction prospect of the energy internet, the electric power internet of things will develop into a system with tightly combined data flow and energy flow. The formation of data flow depends on advanced data sensing, data transmission, data analysis and data sharing technology, and the data flow is a key premise and necessary guarantee for realizing reasonable allocation and management of energy flow, and plays a decisive role in the operation performance of the system. The sensing terminals are deployed on each link of the power grid as comprehensively as possible, data information which is rich and diversified in types is acquired, the information is transmitted to the data platform by means of a data transmission technology which responds in real time and is highly reliable, data mining and fusion analysis are carried out, and analysis results are fed back, so that the requirements of internal services such as planning construction, production decision-making, operation maintenance, monitoring regulation and control, asset management and the like in the process of expanding the power grid construction scale and intellectualization are met.
The 5G technology is a new generation broadband mobile communication technology with high speed, low time delay and large connection characteristics, and is permeated into various fields of various industries of economy and society, and becomes a key novel infrastructure for supporting digitization, networking and intelligent transformation of economy and society, but the research on applying the 5G technology to data processing is relatively less in the prior art. The information is processed by technical means such as an intelligent terminal, a communication network, data processing and the like, so that the 'digital, visual, informationized and networked' of the electric power Internet of things is monitored and managed by utilizing the 5G communication energy, and management personnel can conveniently check and manage energy information. Therefore, a method for solving the problem of low data processing efficiency in a big data environment based on 5G power internet of things monitoring is needed.
Disclosure of Invention
The invention aims to provide a multisource data linking method based on an eSIM card and a 5G network, so as to solve the problems in the prior art.
In order to achieve the above purpose, the present invention provides a multi-source data linking method based on an eSIM card and a 5G network, comprising the following steps:
collecting multi-source data and preprocessing the multi-source data;
transmitting the preprocessed multi-source data based on the 5G base station communication capability and the eSIM card;
and carrying out data link on the multi-source data, and monitoring multi-source data chains such as videos, images, characters, instructions and the like acquired by the power grid asset equipment.
Optionally, the multi-source data is data of different sources, including character type data and non-character type data.
Optionally, the preprocessing the multi-source data includes: unifying the data types in the multi-source data, and grouping the character type data and the non-character type data in the multi-source data.
Optionally, the unifying the data types in the multi-source data includes: classifying the multi-source data according to data types based on keyword matching to obtain classified data of different types; and converting the format of the classified data of different types.
Optionally, the process of transmitting the preprocessed multi-source data based on the 5G base station communication capability includes: and constructing a data sharing server, and uploading the multi-source data of different types to the data sharing server for storage based on a plurality of 5G base stations.
Optionally, the process of data linking the multi-source data includes: judging the relativity of character type data and non-character type data in the multi-source data; based on the correlation, respectively linking the character type data and the non-character type data in a parallel computing mode to obtain a character data chain and a non-character data chain; and acquiring the multi-source data chain based on the character data chain and the non-character data chain.
Optionally, the correlation determination process of the character type data includes: carrying out segmentation processing on the character type data to obtain a plurality of character type data segments; based on a probability linking method, matching the characters in each character type data segment, judging the probability of the same character source, and judging the same character source when the probability of the same two character sources is more than 80%; and carrying out relevance judgment on a plurality of character type data segments based on the number of characters from the same source.
Optionally, the correlation judgment process of the non-character data includes: carrying out segmentation processing on the non-character data to obtain a plurality of non-character data segments; and constructing a correlation recognition model based on a convolutional neural network, inputting the non-character data segments into the correlation recognition model, and outputting the correlation between each non-character data segment.
Optionally, the process of linking the character type data and the non-character type data by adopting a parallel computing mode includes:
ranking the character type data and the non-character type data of each segment according to the size of the correlation; acquiring a first data segment and a last data segment of each group of ranks;
and according to the size of the correlation, taking the first data segment as a starting point, carrying out data link according to the direction from the big to the small of the correlation, and simultaneously taking the last data segment as an end point, and carrying out reverse link according to the sequence from the small to the big of the correlation.
The invention has the technical effects that:
according to the invention, the computation speed of the data link process is improved by preprocessing the multi-source data, the data transmission rate is improved by the 5G power Internet of things monitoring and construction platform, the real-time data transmission processing is realized, the correlation is distinguished by adopting different methods for the data of different character types, meanwhile, a parallel computing data link mode is provided, the generation time of a data link can be greatly saved under the condition of complex data information types, and the data information processing efficiency is improved.
Drawings
The accompanying drawings, which are included to provide a further understanding of the application, illustrate and explain the application and are not to be construed as limiting the application. In the drawings:
fig. 1 is a flowchart of a multi-source data linking method based on an eSIM card and a 5G network in an embodiment of the present invention.
Detailed Description
It should be noted that, in the case of no conflict, the embodiments and features in the embodiments may be combined with each other. The present application will be described in detail below with reference to the accompanying drawings in conjunction with embodiments.
It should be noted that the steps illustrated in the flowcharts of the figures may be performed in a computer system such as a set of computer executable instructions, and that although a logical order is illustrated in the flowcharts, in some cases the steps illustrated or described may be performed in an order other than that illustrated herein.
Example 1
As shown in fig. 1, the embodiment provides a multi-source data linking method based on an eSIM card and a 5G network, which includes the following steps:
data acquisition and transmission
The data collected in this embodiment is data from a plurality of different sources, such as different types of sensors and database lamps, and therefore is referred to as multi-source data, and these data include character attributes and non-character attributes;
after monitoring multi-source data such as videos, images, characters and instructions acquired by power grid asset equipment, preprocessing the data, unifying the types and formats of the multi-source data, wherein keyword matching is a technology for quickly realizing data matching in a large amount of data.
After preprocessing multi-source data, a data sharing server needs to be constructed to realize storage and integration of the multi-source data, meanwhile, in order to improve the transmission speed of the data, a 5G technology is adopted, the multi-source data is transmitted to the data sharing server through a plurality of 5G base stations, a subsequent data link part is completed in the data sharing server, and meanwhile, an eSIM card has the advantages of convenience, high efficiency, low cost and high safety performance, so that the embodiment realizes real-time transmission of the multi-source data through the 5G base stations and the eSIM card, and meanwhile, data link is carried out, so that the processing efficiency of the data is improved.
Data linking
After the multi-source data is transmitted to the server, a linking process is started, in this embodiment, different types of data links are realized through the relevance judgment of the data, and because the multi-source data contains character type data and non-character type data, the character type data and the non-character type data need to be processed respectively, a convolutional neural network is generally used in the fields of voice recognition, natural language processing, target recognition and the like, and a large number of data sets are generally required in the training process of the convolutional neural network and are matched with a large number of multi-source data acquired by the scheme, so that the convolutional neural network is adopted to perform relevance recognition on the non-character type data in the multi-source data in this embodiment. Probability linking is to match and weight multiple fields of two records to obtain probability of the same individual, so as to judge matching between data, so that we adopt probability linking to judge relativity between character data.
In some embodiments, the process of determining the relevance of non-character data using a convolutional neural network includes: carrying out segmentation processing on non-character type data in the multi-source data to obtain a plurality of non-character type data segments; constructing a correlation recognition model based on a convolutional neural network, inputting a plurality of non-character data segments into the correlation recognition model, and outputting the correlation between each non-character data segment, wherein the convolutional neural network in the embodiment comprises an input layer, a convolutional layer, a pooling layer and a full connection layer; the input layer is an input part of multi-source data, the input of each node in the convolution layer is the segmented data in the neural network of the upper layer, the size of each segmented data comprises 3*3 and 5*5, the segmented non-character data are deeply analyzed in the convolution layer to obtain features with higher abstract degree, the pooling layer reduces the dimension of the features extracted by the convolution layer through downsampling, removes redundant information and compresses the features, so that the effect of reducing the calculated amount and the memory consumption is realized, each neuron in the full-connection layer is fully connected with all neurons of the previous layer, the excitation function of each neuron in the full-connection layer adopts a ReLU function, and the full-connection layer is used for integrating and outputting the features extracted by the upper layer neural network structure, namely the correlation among character data segments.
In some embodiments, the process of determining the relevance of character-type data using probabilistic links includes: carrying out segmentation processing on the character type data to obtain a plurality of character type data segments; and based on the probability link, matching the characters in each character type data segment, judging the probability that the two character sources are the same, judging that the matched characters are the same sources when the probability that the two character sources are the same is greater than 80%, and finally judging the correlation of a plurality of character type data segments according to the number of the characters of the same sources, wherein if the number of the characters of the same sources is the largest, the correlation of the two character type data segments is the highest, otherwise, the correlation is the lowest.
After the correlation judgment of the character data and the non-character data is completed, the invention provides a parallel computing mode for respectively linking the character data and the non-character data, which comprises the following specific steps:
and ranking the character data and the non-character data according to the size of the correlation, and acquiring the first data segment and the last data segment of each group of ranking after the ranking is completed.
And according to the size of the correlation, carrying out data link by taking the first data segment as a starting point and carrying out reverse link by taking the last data segment as an end point according to the direction from the big to the small of the correlation and carrying out reverse link according to the sequence from the small to the big of the correlation.
After the steps are finished, a character data chain and a non-character data chain can be respectively obtained; and finally, monitoring a multi-source data chain such as video, images, characters and instructions acquired by the power grid asset equipment according to the character data chain and the non-character data chain, and completing the linkage of the multi-source data.
According to the method, the computing speed of a data link process is improved by preprocessing the multi-source data, the data transmission rate is improved by the 5G power Internet of things monitoring and constructing platform, real-time data transmission and processing are achieved, correlation is distinguished by different methods for data of different character types, a parallel computing data link mode is provided, the generation time of a data link can be greatly saved under the condition that the data information types are complex, and the data information processing efficiency is improved. It can be seen that the present invention has outstanding substantial features and significant advances over the prior art, as well as its practical advantages.
The foregoing is merely a preferred embodiment of the present application, but the scope of the present application is not limited thereto, and any changes or substitutions easily contemplated by those skilled in the art within the technical scope of the present application should be covered by the scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.
Claims (5)
1. A multi-source data linking method based on an eSIM card and a 5G network, comprising the steps of:
collecting multi-source data and preprocessing the multi-source data;
transmitting the preprocessed multi-source data based on the 5G base station communication capability and the eSIM card;
carrying out data link on the multi-source data, and monitoring multi-source data chains such as videos, images, characters, instructions and the like acquired by power grid asset equipment;
the process of data linking the multi-source data comprises the following steps:
judging the relativity of character type data and non-character type data in the multi-source data;
based on the correlation, respectively linking the character type data and the non-character type data in a parallel computing mode to obtain a character data chain and a non-character data chain;
acquiring the multi-source data chain based on the character data chain and the non-character data chain;
the correlation judgment process of the character type data comprises the following steps:
carrying out segmentation processing on the character type data to obtain a plurality of character type data segments;
based on a probability linking method, matching the characters in each character type data segment, judging the probability of the same character source, and judging the same character source when the probability of the same two character sources is more than 80%;
performing relevance judgment on a plurality of character type data segments based on the number of characters from the same source;
the correlation judgment process of the non-character data comprises the following steps:
carrying out segmentation processing on the non-character data to obtain a plurality of non-character data segments;
building a correlation recognition model based on a convolutional neural network, inputting the non-character data segments into the correlation recognition model, and outputting the correlation between each non-character data segment;
the process of linking the character type data and the non-character type data by adopting a parallel computing mode comprises the following steps:
ranking the character type data and the non-character type data of each segment according to the size of the correlation; acquiring a first data segment and a last data segment of each group of ranks;
and according to the size of the correlation, taking the first data segment as a starting point, carrying out data link according to the direction from the big to the small of the correlation, and simultaneously taking the last data segment as an end point, and carrying out reverse link according to the sequence from the small to the big of the correlation.
2. The eSIM card and 5G network based multi-source data linking method of claim 1, wherein the multi-source data is data of different sources including character type data and non-character type data.
3. The eSIM card and 5G network based multi-source data linking method of claim 1, wherein the preprocessing of the multi-source data comprises:
unifying the data types in the multi-source data, and grouping the character type data and the non-character type data in the multi-source data.
4. The eSIM card and 5G network based multi-source data linking method of claim 3, wherein unifying the data types in the multi-source data comprises:
classifying the multi-source data according to data types based on keyword matching to obtain classified data of different types;
and converting the format of the classified data of different types.
5. The eSIM card and 5G network based multi-source data linking method of claim 1, wherein the transmitting the preprocessed multi-source data based on the 5G base station communication capability comprises:
and constructing a data sharing server, and uploading the multi-source data of different types to the data sharing server for storage based on a plurality of 5G base stations.
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