drowning-detection

Drowning Detector - A computer vision project using OpenCV and deep learning to detect drowning incidents in videos.

High-efficiency Drowning Target Detection System 🏊

Automated Drowning Detection: A repository showcasing a deep learning-based solution using YOLO v8 architecture for swift and accurate identification of drowning instances in aquatic environments. Enhanced accuracy through meticulous fine-tuning and integrated methodologies. Empowering drowning incident response systems for improved efficiency.

detect drowning probability in swimming pool

Training swimming style recognition

A pool camera that warns when someone stays out of sight too long. RF-DETR fine-tuned on real pool footage, a multi-object tracker that keeps one ID per swimmer, and drowning scenarios built in NVIDIA Isaac Sim and MuJoCo because they can't be filmed.

Swimming style recognition application with android wear os

TCC: Detecção de afogamento em piscinas com YOLO (yolo11n, yolo26n, yolo26s) — Visão Computacional

SmartPool · 智慧泳池溺水实时防护系统，基于 Mamba-YOLO 的检测、分级预警与处置闭环平台

Drowning detection for public swimming pools: multi-camera 3D tracking through the water surface, ISO 20380 rules and lifeguard alarms - 200/200 simulated ISO tests, 0 false alarms.

🏊‍♂️ Swimming pool safety monitoring — Detect unsafe behaviors (diving in shallow areas, overcrowding) and drowning

🏊 Drowning detection system — Monitor swimming pools and beaches for drowning incidents with instant alerts

Drowning device using a custom YOLOv11n model, Raspberry Pi, and AI camera

A lightweight real-time drowning detection model that runs on a low-cost edge devices, designed for deployment in low-income regions.

🏞️ Riverbank child safety monitoring — detect children near riverbanks and water edges to prevent drowning accidents with real-t

A Raspberry Pi–based drowsiness detection system that watches for eye closure using computer vision and sounds an alarm when the driver appears sleepy. Built as a simple, real-time safety project to help reduce fatigue-related accidents.

Detecting signs of drowning from above-water pool cameras. Detects and tracks every swimmer, extracts pose, and flags anomalous behavior; synthetic Blender data and fine-tuned detectors are the current area of focus.

AI-powered drowning detection demo using YOLOv8