Undergraduate YPEC 2022

UG16 – Artificial Intelligence Swimming Pool Drowning Detection and Rescue System by IoT

In response to drowning, some companies developed a system to alert and support the lifeguard in observing the drowning people underwater. However, these applications focus on the alert upon identifying victims who are already drowning. On the other hand, our Swimming Pool Drown Detection and Rescue System focuses on the entire supporting architecture. We focus on identifying pre-drown victims with an active rescue system. In our system, each swimmer will be given a wearable device to measure and detect any abnormal physical conditions by monitoring blood oxygen level and heart rate. When an abnormal signal is detected, the web application will alert the lifeguard and shoot a lifebuoy to the victim’s location under the lifeguard’s attention. By no means we would like to replace the lifeguard with a computer. Our system architecture would further focus on the indoor 25-meter training swimming pool setting, which is the most common pool type, which enables a better focus of the rescue system on fundamental functionality and maximizing the possible usage. However, due to the n-CoV situation during the development of the project, our evaluation is further confined to the 3m*2m pool located at HKUST.