| dc.description.abstract | Swimming, is a prominent sport in Sri Lanka
with a significant number of school, university, and open-
level swimmers participating in competitions. However, the
management of these events faces critical challenges, due
to outdated manual processes. Current systems rely on
physical form submissions, in-person payments, and
delayed access to meet schedules and heat assignments,
with limited integration of performance data. This research
introduces AQUAFINA, a comprehensive digital platform
designed to address these inefficiencies and enhance
athlete management. The aim of AQUAFINA is to automate
meet registrations, facilitate online payments, and provide
real-time access to meet schedules and heat assignments.
Additionally, the system incorporates a machine learning-
based performance prediction tool, utilizing historical
performance data, physical metrics, and training records
to forecast swimmer results, and facilitates a collaboration
platform for swimmers and coaches to interact with each
other. This integration addresses gaps identified in existing
literature, which highlights the limitations of current
systems in performance prediction, swimmer-coach
collaboration, and comprehensive meet management.
Methodologically, AQUAFINA employs a web-based
platform integrating these features, with an emphasis on
improving efficiency, transparency, and collaboration. In
conclusion, AQUAFINA provides a comprehensive, data-
driven solution to improve the efficiency of swimming
competition management and swimmer-coach
collaboration for swimmers of all levels in Sri Lanka | en_US |
