Document Type

Capstone Open Access

Faculty Supervisor

Rogerio de Leon Pereira

Date of Defense

Fall 12-6-2024

Department

Faculty of Applied Science & Technology (FAST)

Program Name

Honours Bachelor of Computer Science (Mobile Computing)

School

Applied Computing

Description

Golf Swing Trainer is a wearable focused solution that leverages mobile and IoT devices as well as their sensors to provide an accessible way for users to improve their gameplay.

Abstract

The advent of mobile technology and smartwatches has revolutionized sports training, including golf. This abstract presents an innovative golf training app that harnesses the power of these devices to enhance golfers' skills. The proposed app integrates mobile device capabilities to track and record a golfer's swing, generating a detailed 3D model for comprehensive analysis. Concurrently, a smartwatch with built-in sensors, including the accelerometer, captures precise swing data. Leveraging machine learning algorithms, the app processes the smartwatch's recorded swing data to provide insightful tips and personalized recommendations, aiding golfers in refining their technique and improving their overall game. This integrated approach offers an advanced and accessible tool for golf enthusiasts seeking to elevate their golfing proficiency through data-driven insights and actionable feedback.

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