Design of Aquatic Ecology Intelligent Monitoring System for Urban Lake

Traditional lake monitoring methods are costly and inefficient, and the low utilization of multi-source heterogeneous monitoring data further compounds the inability to meet the monitoring and governance needs for lakes. To address these pressing challenges, establishing an aquatic ecology intelligent monitoring (AEIM) system for the aquatic ecology of urban lakes is crucial. Targeting the integration of advanced monitoring technologies and the efficient processing of heterogeneous datasets, this paper proposes a ubiquitous design for an AEIM system and presents its architecture and functional design. In the design of the system's main functional modules, a multidimensional aquatic ecological assessment framework and water pollution early warning mechanism based on water quality prediction model, were utilized in order to achieve the goals of assessment and early warning. Furthermore, the monitoring network and application software design are discussed, with Wuhan East Lake serving as a case study. The proposed system has demonstrated its ability to enhance information utilization and improve the efficiency of monitoring urban lake ecosystems.