Development of Intelligent Analysis and Visualization Software Tools for Environmental Monitoring Data

With the increasingly severe environmental pollution problem, the widespread deployment of environmental monitoring stations has generated massive and complex environmental data. Traditional data processing methods seem inadequate in the face of such a large amount of data, while the introduction of big data technology has brought revolutionary changes to the processing and analysis of environmental monitoring data. Through big data analysis, not only can the accuracy and completeness of monitoring data be significantly improved, but also the efficiency and quality of environmental monitoring can be greatly improved, providing solid data support and scientific decision-making basis for environmental management departments. This article focuses on developing an efficient and intelligent software tool for analyzing and visualizing environmental monitoring data, aiming to meet the high requirements for data processing and display in current environmental protection work. This software deeply integrates big data analysis and deep learning (DL) technology, and achieves intelligent mining and deep analysis of environmental monitoring data by constructing advanced algorithm models. The experimental results show that the software can accurately identify environmental change trends, predict potential pollution events, evaluate environmental quality levels, and present the analysis results to users in an intuitive and understandable visual form.

I. Introduction

In the 21st century, the acceleration of industrialization and the sweeping wave of urbanization not only greatly promote the rapid development of the social economy, but also bring unprecedented ecological and environmental challenges [1]. Faced with this global crisis, environmental protection has become a focus of attention for governments and various sectors of society [2]. With the advancement of technology, especially in the fields of computer technology, control technology, Internet of Things (IoT), and artificial intelligence (AI), unprecedented technological support and solutions have been provided for environmental monitoring and governance [3]. The rise of smart home systems marks a further improvement in human requirements for the quality of living environment [4]. By integrating various sensors and intelligent devices, real-time monitoring of key indicators such as indoor air quality, temperature and humidity, and light intensity can not only provide real-time feedback on the comfort of the living environment, but also effectively alert potential sources of pollution, creating a healthier and safer living space for residents [5].