To Detect Active Drowning Using Deep Learning Algorithms

One of the best workouts for stress reduction in the modern metropolitan lifestyle is swimming. Fewer people have swimming pools in their backyards, they are more common at hotels and weekend tourist destinations. Beginners, in particular, frequently struggle to breathe underwater, resulting in respiratory. Drowning causes a higher mortality rate worldwide while causing no harm to children. The highest global drowning fatality rates are observed to be among children under the age of six. With around 1.2 million incidents each year, these types of deaths rank third among all unexpected deaths worldwide. A careful system is to be implemented along the swimming pools tosave lives to resolve this dispute. Swimmers' safety depends on effective drowning detection techniques. Drowning is the third most common cause of unintentional fatalities, according to WHO data. The development of a drowning detection system is becoming increasingly important to ensure the safety of swimmers, particularly children. Theproposed solution detects drowning consistently wellregardless of pool depth, water characteristics, or the number of people in the pool. A motion average is determined for the last ten sensor readings. The moving average values are then compared to a predefined threshold value. To settle this argument, a strict mechanism must be installed next to the swimming pools to protect human life