In environments like swimming pools and water parks, the challenge of drowning prevention has never been just about "seeing" — it is about "seeing accurately." Surface reflections, ripples, the wide variety of swimmers' body movements, and lifeguards constantly walking around all cause ordinary cameras to generate numerous false alarms. Frequent alerts not only drain lifeguards' attention but also, over time, desensitize them to warnings, potentially causing real dangers to be overlooked. Therefore, a reliable drowning prevention system must first reduce its false-positive rate.
Our AI algorithm was designed from the start around real aquatic scenarios. Instead of simply applying a generic behavior recognition model, it has been specially optimized for the long-term visual characteristics of swimming pools and water parks. The algorithm can distinguish normal actions such as swimming, splashing, diving, and floating on the back, while also recognizing high-risk postures like "no movement for an extended period," "head continuously below the surface," and "abnormal sinking." More importantly, it makes comprehensive judgments by combining temporal and spatial context — for instance, a child remaining still in the water for two seconds might just be holding their breath, but an alert is triggered only when stillness exceeds a certain threshold and is accompanied by specific postures. This multi-dimensional reasoning logic greatly reduces invalid alarms caused by synchronized swimming, water ball tossing, or light refraction.
In actual deployment, the system also features scene-adaptive capabilities. Indoor temperature-controlled pools and outdoor water parks differ greatly in lighting conditions, water color, and crowd density. The algorithm supports calibrating sensitivity individually for different camera locations. Operators can flexibly set alarm thresholds based on the risk level of each area, ensuring both that dangers are detected promptly and that lifeguards do not become mere "alarm watchers." At the same time, alert notifications are pushed directly to wristbands worn by lifeguards or terminals in the duty room, along with real-time screenshots and location annotations for immediate verification and response.
We do not claim that this algorithm can replace lifeguards' professional judgment. Its value lies in serving as an untiring pair of eyes, covering the brief moments of distraction or blocked sightlines that can occur during manual patrols. Low false-positive rates mean that every alarm is worth taking seriously, allowing technology to truly return to its essence of assisting people and safeguarding lives. For pool operators, this is not merely an equipment upgrade but a genuine responsibility toward every visitor.