Intelligent water affair data center station based on distributed cloud architecture

Abstract

An intelligent water affair data center station based on a distributed cloud architecture comprises a data collection layer, a data background layer, a service center station layer, a foreground application layer and an interaction layer, wherein the data collection layer has standardized access to data of an informatization system of each regional project in an API mode and collects data of external terminal equipment; wherein the data background layer comprises a basic database and a secondary processing database, the service center station layer processes basic data collected by a data background through a data processing tool, and the foreground application layer comprises a comprehensive display application, a project management service, a safe operation service, an evaluation serviceand a universal service. The interaction layer comprises a browser, a WeChat applet and a WeChat official account. Interaction tools comprise a large screen, a computer, a tablet personal computer and a mobile phone. According to the invention, standardized acquisition, storage, management, analysis, mining, sharing, exchange, display and application of water affair data of group-level-project-level multi-management-level projects can be realized.

Description

Technical field[0001]The present invention relates to the technical field of water affairs industry informatization, in particular to a smart water affairs data center station based on a distributed cloud architecture.Background technique[0002]The urban water environment system includes the integrated business links of "raw water-water delivery-water production-water supply-water use-drainage-sewage", and the information involved is spatial, complex, analyzable, timeliness, multi-source and data It is the most valuable data resource for water environment assessment, management and decision-making. Because this information has the characteristics of space, complexity, analyzability, timeliness, multi-source and large amount of data, it is the most valuable data resource for water environment assessment, management and decision-making. However, due to the lack of an effective organization and management model, water companies have inconsistent data collection standards for the constru...

AI Technical Summary

Problems solved by technology

However, due to the lack of effective organization and management models in water enterprises, the data collection standards for the construction of information systems are not uniform, and there are large differences in application requirements for each project, the functions of each subsystem are single, the software docking is difficult, and the degree of integration is poor. Data sharing is difficult, and data value cannot be effectively discovered and utilized

[0003] The current water enterprise informatization system has the following deficiencies summarized as follows: First, each business system is centered on its own single application, resulting in inconsistent data standards, data islands, difficult integration, poor scalability, and mismatched management granules; In terms of technology, informatization assets and capabilities have not been effectively accumulated, and the degree of service and reuse of business and data in the system is low. The development of new systems or functional modules basically needs to start from scratch, and data analysis needs to be oriented to original data, resulting in poor system flexibility. 1. The construction period is long, the cost is high, and it cannot support the construction of a modular service model; the third is that the data analysis application is not systematic and has a single function, which cannot meet the needs of personalized data analysis applications

[0004] At present, there is no water information platform based on the distributed deployment of multi-regional projects, which can solve technical problems such as standardized collection, storage and management, analysis and mining, sharing and exchange, presentation and application of enterprise data.

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