Nowadays swimming pools is considered one of the main luxuries in the world right now and can be found in clubs, residents, hotels, and schools. Most of these places have a lifeguard to keep an eye on swimmers and rescue them if an accident happens but lifeguards always face difficulties like swimmers who drown in blind spots, So we propose a system based on IOT technology that classifies swimmers behavior underwater and switches on alerts if the system detects a drowning behavior. The system consists of main 3 nodes. The camera captures videos underwater with microcontroller “nividea jetson”. As a result,Drowning is detected using machine learning, image processing techniques and CNN algorithm. Finally, a mobile message notification will be sent to the medical support account on the mobile application and additionally, a light alarm will alert the pool. 

Our objective is to build a real-time system that will track swimmers to alert any possible drowning occurs in an early stage by detecting drowning behavior and create a dataset of a drowning behavior and normal behavior that can be used by other engineers to create their own system or improve our one.

1. The system shall track swimmers using a camera placed underwater.

2. The system shall detect the drowning behavior of the swimmer.

3. The system will have medical support users.

4. The system will alert the lifeguards whenever the probability of someone drowning is high.