Introducing our drowning detection system, designed to detect and alert when someone is in danger of drowning. Our system uses computer vision algorithms to analyze video feeds from multiple cameras around a pool or other bodies of water.

Our method uses a HSV thresholding mechanism along with Contour detection to detect the region of interest in each frame of video sequences. The presented software can detect drowning person in indoor swimming pools and sends an alarm to the lifeguard rescues if the previously detected person is missing for a specific amount of time.

The latest technology advancement have enables to come up with effective drowning detection methods. This project uses CNN architecture to classify different object with their dimension (In general height and width of the object),so we detect human from the video frame ,then we calculate height and width for that object. If the swimmer

Dec 30, 2022 · This project aims to create a system that will be able to automatically detect drowning incidents in the swimming pool using human action detection. The drowning detection model...

The proposed system structure comprises raspberry pi (Single Board Computer) equipped with a USB camera for taking the live feed from the pool area. The system also covers the alerting phenomena using a buzzer so that necessary actions are taken intermittently without any delay.

Mar 8, 2018 · This document describes an automated system to detect drowning incidents in swimming pools. The system uses differential pressure sensing to monitor pressure changes when someone enters the water. A pressure sensor worn on the wrist transmits data to a receiver module at the pool site via RF.

Swimming pool surveillance systems plays an essential role in safeguarding the premises. In this project differential pressure approach is used for detection of drowning incidents in swimming pools at the earliest possible stage. The children’s life is saved during drowning incidents in the swimming pool by lifting the acrylic plate. The

This project provides the insights of a real-time video surveillance system capable of automatically detecting drowning incidents in a swimming pool. Drowning is the 3rd reason for the highest unintentional deaths, and that’s why it is necessary to create trustable security mechanisms.

This project provides the insights of a real-time video surveillance system capable of automatically detecting drowning incidents in a swimming pool. Drowning is the 3rd reason for the highest unintentional deaths, and that's why it is necessary to create trustable security mechanisms.

This project introduces an innovative approach to drowning detection, leveraging the capabilities of the Internet of Things (IoT) and a sophisticated array of sensors. Drowning, often swift and silent, necessitates a proactive and