Water quality monitoring data analysis method and system based on sponge city

By constructing a layered architecture and using tools such as Apache Spark and Flink for preprocessing, storing, and deeply analyzing water quality monitoring data, the problem of real-time processing of water quality monitoring data was solved, achieving efficient and accurate data analysis and visualization, and providing technical support for sponge cities.

CN122087004APending Publication Date: 2026-05-26BEIJING HUAZHAN HUIYUAN INFORMATION TECH CO LTD +1
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Patent Information

Application Number
CN202511920149.6
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2025-12-18
Publication Date
2026-05-26

AI Technical Summary

Technical Problem

Existing technologies lack effective data preprocessing mechanisms in water quality monitoring. Storage solutions have high hardware requirements and poor scalability, resulting in low data processing efficiency and limited accuracy, making it difficult to meet the real-time processing needs of massive amounts of water quality monitoring data.

Method used

A hierarchical architecture for water quality monitoring data analysis and processing was constructed. Data was collected through a Kafka message queue, preprocessed and stored, and batch and streaming processing was performed using Apache Spark and Apache Flink. In-depth analysis was conducted in conjunction with a query engine, and data model parameters were iteratively optimized to generate visualization results.

Benefits of technology

It improves the efficiency of data collection and analysis, enhances the accuracy and intelligence of results, reduces hardware requirements and operating costs, and supports water quality management in sponge cities.

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Abstract

The invention relates to a water quality monitoring data analysis method and system based on a sponge city, and the method comprises the steps: responding to an analysis demand and range, and constructing and configuring a water quality monitoring data analysis processing layered architecture; collecting water quality monitoring data and carrying out pretreatment and storage treatment; performing batch processing on the static data, and / or performing streaming processing on the real-time dynamic data to generate a preliminary analysis result; importing the preliminary analysis result into a pre-constructed data model for processing, and iteratively optimizing parameters of the corresponding data model and algorithm parameters deployed by the data model; and actual monitoring data after a deep analysis result output by the application data model is observed and tracked, the architecture is actually optimized and adjusted, and a data result is converted into a visual form, encrypted and provided for an access object. The full-automatic management process provided by the invention not only improves the efficiency of data acquisition and analysis, but also greatly enhances the accuracy and intelligent level of the result, and reduces the supervision cost.
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