The pandemic has struck people’s life in various factors, such as limited mobility that caused people to stay at home which made them unhealthy and unfit. After the pandemic, people started to prioritize their health as their main concern. Therefore, numerous individuals came to a place where they could train their bodies and maintain their health by going to the gym. A gym is a place for indoor physical workouts where various equipment and machines are typically used. However, beginners in the gym face challenges in identifying and properly using gym equipment, which can lead to frustration and the risk of injury.

To address this problem, we propose the development of an Android application that utilizes Machine Learning (ML) to detect and identify gym equipment and provide easy-to-follow instructions on how to use them correctly. The application will use machine learning algorithms and computer vision techniques to recognize and analyze gym equipment movements, providing instructional videos that demonstrate the proper form and technique for each exercise.

In addition, the application will also provide the nearest gym to the users so the users could easily reach the closest gym and start their workout. This technology would provide a user-friendly interface that can be accessed on a smartphone or tablet, allowing them to quickly and easily learn how to use gym equipment, reducing the risk of injury and enhancing their overall gym experience.