In recent years, with the rising popularity of coastal tourism, the pressure on beach safety management has also grown significantly. Especially in large open-water areas, relying solely on lifeguard lookout and traditional patrols makes it difficult to achieve real-time control over every risk point. Recently, some beach scenic areas have begun introducing AI drowning prevention systems to fill the blind spots of manual inspection through technological means. How has this system actually performed in real-world deployment, and what experience has been gained?
The core logic of this AI system is not complicated: through high-definition cameras and edge computing devices installed on the shore, it analyzes swimmers' postures and movement trajectories in the water in real time. Once suspicious drowning characteristics are detected—such as the head remaining submerged for a long time, abnormal struggling, or drifting with the waves without autonomous movement—the system sends an alert to the command center within seconds and simultaneously pushes location information. Compared with the traditional call-and-search model, the greatest advantage of this solution is early detection, especially in poor visibility at dusk, crowded shallow water areas, or open sea sections with strong waves, where it can help lifeguards quickly pinpoint targets.
During actual deployment, the challenges posed by large water areas are far more complex than imagined. Sea surface glare, sudden weather changes, wave spray blocking the view, and the diverse swimming postures of visitors can all easily lead to false alarms or missed detections. Therefore, the project team did not simply install a few cameras and call it done; instead, they repeatedly adjusted the algorithm models and camera angles based on each beach's hydrological characteristics and key area divisions. Some scenic areas have also adopted a dual-confirmation mechanism of AI warning plus manual review: after the system issues an alert, duty personnel perform a second confirmation on the monitoring screen before notifying the nearest lifeguard to act, thereby reducing the interference of false alarms while ensuring no real danger is missed.
From the initial results, this system plays more of an auxiliary sentinel role. It cannot replace lifeguards' professional judgment and on-site rescue capabilities, but it does significantly shorten the time window for risk detection. Especially in traditionally weak monitoring zones such as open beaches, rocky interlaced areas, or rip-current-prone sections, the AI's continuous scanning ability compensates for the weakness of visual fatigue. For scenic area managers, the value of such practice lies not only in installing smart devices, but also in forming a collaborative flow of machine inspection, manual confirmation, and rapid rescue. With continuous algorithm iteration and the accumulation of more beach data, AI drowning prevention systems are expected to become an increasingly reliable part of coastal safety infrastructure.