Consistency data collection method and system

Abstract

The invention relates to a consistency data collection method and system. The method comprises the steps that S1, collecting supervision data in a corresponding collection mode by a collection front end; s2, storing the collected data in a data storage unit according to a first mode; s3, acquiring data according to a second mode bya submission unit; and S4, carrying out data processing based on the data obtained in the step S3 bya supervision unit. Through physical collection consistency and non-semantic consistency judgment, the accuracy, fairness, safety and consistency of data collection can be guaranteed, Meanwhile, the data processing efficiency can also be guaranteed.

Description

【Technical field】 [0001] The invention belongs to the technical field of data processing, and in particular relates to a consistent data collection method and system. 【Background technique】 [0002] The Internet of Things is a network that connects any item to the Internet on the basis of the computer Internet for information exchange and communication, so as to realize the intelligent identification, positioning, tracking, monitoring and management of items. However, network data transmission technology is widely used in various industries. Sometimes network data needs to be supervised. Sometimes in the process of supervising data transmission across industries or regions, due to industry or regional policies, regulatory principles, methods and regulations do not match. , resulting in unregulated phenomena. The method of data collection based on the Internet of Things can carry out back-end processing of industry data in various industries; for example: in the provident fu...

AI Technical Summary

Problems solved by technology

However, the existing data collection methods are solidified, and the collection front-end often adopts a relatively primitive way of passive collection, and the collection content will also change due to different collection methods, and different supervision requirements correspond to a large amount of repeated data; for example: when discovering supervision requirements After the change occurs, artificially change the collection method; another more serious problem is that the data collection lacks consistency, and the data collection is very subjective, which leads to poor actual monitoring effect; how to make the data internally consistent is also a problem. It means that the data essence is consistent with the collected data, the data acquisition method ensures that the data content does not change, how to ensure that the collected data is consistent with the final processing requirements, how to fully utilize duplicate data, and how to make each node of the processing process and its corresponding users Consistency, how to ensure that the scope of data acquisition and user functions are consistent is a problem that needs to be solved, which involves data security, data acquisition architecture, data utilization and other aspects

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