Honors

I was the leader of my team, who placed third in a competition analyzing 5 years of school accident cases to present ideas for preventative methods

Using Python, Pandas library, and Matplotlib libraries, I processed data from spreadsheets and visualized the trends to gain insights. The analysis revealed an increasing accident rate during gym hours. This prompted a deeper focus on analyzing safety incidents related to gym activities.

Linking Python with Excel and using Pandas for data manipulation, I was able to create informative graphs with Matplotlib. Focusing on gym-related incidents, the analysis revealed nearly half of the accidents in 2023 were caused by exercise equipment, with most incidents involving physical force, sprains, falls, and ball games. These findings suggested that student carelessness and a lack of safety education were key factors.

Based on this analysis, I proposed three solutions: First, a student monitoring system using smart devices to track heart rates and movements during PE classes, allowing teachers to ensure proper warm-up and respond to emergencies. Second, the use of VR simulations to train students in agility, ball game scenarios, and accident response, preparing them for unexpected situations and reducing the risk of secondary injuries. Finally, an AI-powered exercise equipment detection system with cameras would analyze student movements and provide voice guidance to prevent accidents, even when teachers are not present. Together, these solutions leverage technology to enhance safety awareness and reduce accident rates in schools.

While it was difficult to deduce creative solutions unique from those presented in the past, I found my data analysis to be critical in this process.

To share my solutions, I created a presentation to pitch my ideas to the professors and the head of the Korean Education Organization. This concluded with success as these authorities complemented my utilization of code to solve this problem with technology. This was a valuable experience for me as this was an opportunity to analyze big data to deduce a solution. In analyzing 700,000 school accident cases in Korea, I focused on causes, injury locations, and accident sites. Through this process, I discovered that details I had previously disregarded – such as time and day – were critical. Noticing that most accidents occurred during unsupervised lunchtime, I once against felt the importance of considering all data equally to recognize problems and provide accurate solutions.