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Abstract

According to the International Life Saving Federation (ILSF) around 1.2 million people die from drowning every year. More interestingly, the ILSF believes that 8 to 10 times that many people are rescued from dangerous surf conditions by friends or lifeguards. This paper seeks to address water safety by using data analysis to better understand what conditions lead to greater rescues at the beach. The analysis uses a database of daily summer rescue numbers along with weather and wave conditions. This data was compiled over 8 years by the Bethany Beach Patrol in Bethany Beach, Delaware. The data is used to test several methods of forecasting. These methods include Auto-regression and machine learning models. The final goal is identifying trends that create a better understanding of how weather and waves can affect human behavior and what conditions are more dangerous in general. This study takes a new angle in the research surrounding water safety. The results could greatly impact public safety of beach goers in the United States and around the world.