Under the impetus of digital transformation, the water conservancy sector is undergoing unprecedented changes. SuperMap actively explores the deep integration of AI technology with digital twin for water conservancy. Leveraging the robust capabilities of geospatial intelligence software, SuperMap has established an integrated "Sky-Ground-Water-Engineering" management system. This system enhances intelligent monitoring and perception across all elements of water conservancy objects and the entire governance process, providing strong computational data support for the high-fidelity construction and operation of digital twin water conservancy.
Sky-Eye: Global Monitoring and Dynamic Perception
SuperMap combines AI technology with remote sensing satellite monitoring to enable intelligent interpretation of high-precision remote sensing images. It automatically identifies key information such as water body boundaries, vegetation coverage, and land-use changes, offering critical data support for water resource management and disaster early warning.
For example, in Beijing's Tongzhou District, SuperMap utilizes high-resolution remote sensing imagery to identify and regulate urban black-odor water bodies. Through a four-step workflow: 1) image (pre)processing; 2) suspected black-odor water identification; 3) field verification; 4) result mapping, the system directly extracts black-odor water bodies, providing insights into the current status and evolution of water areas in Tongzhou.
Aerial Guardian: Capturing Hydrological Dynamics
Leveraging LiDAR, weather radar, and rainfall measurement radar, SuperMap integrates drone video data with geospatial information and to monitor small-to-medium-scale dynamics in key areas such as shoreline zones and flood detention basins. Coupled with AI-powered analysis, the system detects real-time surface changes to assist precise decision-making for reservoir management and flood control, achieving intelligent aerial monitoring.
Ground Sensors: Precise Perception of Hydrological Elements
SuperMap employs multi-zoom surveillance cameras to capture small-scale real-time videos. By deeply integrating video, AI, and water conservancy operations, it assists in tasks like gauge recognition, water level analysis, and sluice gate monitoring. The system automatically identifies anomalies such as abnormal water level rises, water pollution, infrastructure damage, and dike breaches, issuing real-time alerts to secure critical response time.
Automatic Identification and Early Warning
In the Yilong Lake Basin Smart Monitoring Platform project, SuperMap’s AI-powered lake patrol system combines high-definition remote sensing imagery, real-time video, AI recognition models, and behavioral analysis to automatically detect regulatory violations and safety risks. Features like auto-photography and screenshot evidence collection enable digital lake patrols.
Water State Insight: Accurate Prediction and Intelligent Decision-Making
To meet flood prevention demands, SuperMap employs AI and deep learning models to analyze historical and real-time hydro-meteorological data, enabling precise monitoring of rainfall and groundwater levels. SuperMap seek to integrate hydrological principles with data-driven models, embedding physical mechanisms of watershed runoff generation and flow concentration to ensure predictions align with natural laws.
Engineering Safeguards: Ensuring Infrastructure Security
SuperMap applies AI monitoring and big data-driven deep learning models to hydraulic engineering. Utilizing devices like osmometers, fiber Bragg gratings, and multi-zoom cameras, the system integrates GIS and AI algorithms to achieve real-time, high-precision monitoring of seepage pressure, deformation, stress-strain, water levels, and gate operations in dams, embankments, and sluices. This provides scientific support for maintenance and emergency repairs, advancing intelligent and refined engineering oversight.
