Development and Prospect of Water Quality Monitoring Technology Driven by Data-model Coupling - ZHU Lijie; HE Kai; HUANG Sheng; YIN Qidong; DAI Chao (Renmin Zhujiang)
With the advent of the big data era, water quality detection technology has rapidly advanced, transitioning from traditional manual testing to new real-time monitoring and system management. Currently, big data technology has been widely applied in various aspects of water quality monitoring, including data collection, real-time monitoring system, data storage and management, data analysis, and risk assessment. Wireless sensor networks and remote sensing have gradually become the mainstream technologies for data collection, while the further use of cloud platforms and various databases has enhanced the development of real-time water quality monitoring. Moreover, the hybrid storage of spatio-temporal big data has significantly improved data storage efficiency. In terms of water quality analysis and prediction, artificial intelligence techniques, such as machine learning and expert systems, have played a significant role. In the future, big data will further facilitate the development of water quality monitoring by integrating with such emerging technologies as the Internet of Things (IoT), upgrading equipment integration, and developing hybrid machine learning models.