Edge AI Computing and machine learning now enable efficient, accurate, and fully on-site monitoring and analysis of hydrological data — including water level, sediment level, flood prediction, and local meteorological information — without relying on cloud resources. By preforming machine learning inference at the edge, the system transforms traditional static sensors into adaptive, intelligent instruments. This shift moves beyond conventional threshold rules toward data-driven predictive intelligence, establishing a new benchmark for smart city and climate-resilience infrastructure.
Paired with NEXCOM Smart Staff Gauge, it enables near real-time EC profile data collection and transmission at multiple depths in specific locations within a water body. These EC variations, combined with concurrent water-level changes, provide early and reliable indicators of river dynamics.