Analysis of Mobile Accelerometer Sensor Movement Using Machine Learning Algorithm

Currently, many mobile phones come equipped with sensors that enable the delivery of advanced features and services to users. One type of sensor that is commonly embedded in mobile phones is the accelerometer. By applying machine learning algorithms to analyze the movement patterns of a mobile device through its accelerometer data, valuable insights can be gained. This analysis can classify different types of movement, such as walking, running, or driving. These insights can be applied in various settings, such as providing better fitness tracking apps and developing new methods for user authentication. The purpose of this research is to explore and examine the movement patterns of mobile devices through the application of machine learning techniques to accelerometer sensor data.