Abstract:
Humans were able to swim for a long period of time, long enough where nobody knows
when someone swam for the first time. Because of this human nature still, we try to swim
in every chance we get. Due to the increasement of the population and growth of cities,
people tend to swim at swimming pools because of their busy schedules. Because of that,
swimming pools are becoming a must factor for hotels, restaurants, apartment complexes,
and even for some houses. Even though the number of swimming pools increases along
with the population, lifeguards are not getting assigned to those places. That makes a
major life threat to swimmers.
To avoid that a proper solution needed to be found. By surveying lifeguards and simmers
and doing a literature survey. Early drowning detection methods were found. Combining
those with computer vision and machine learning a prototype was created to detect
drowning incidents before such an incident happens.
That prototype was tested and evaluated by professionals and identified future
enhancements as well. Methods were found to increase the accuracy and those were
documented in the thesis.
