Human Activity Recognition using Smartphone Dataset: A Review

Cell Phones are becoming more refined with each new model release. These days phones ordinarily consolidate numerous sensors for various functions such as GPS tracking, temperature sensors, accelerometer, gyroscope, high-determination cameras. In recent years, Human Activity Recognition (HAR) has enabled various applications. The information gathered by HAR may be utilized for a number of reasons, including fitness tracking, health and safety, and entertainment, among others. An abundance of research has been conducted on real-time processing, which has resulted in increased power consumption of mobile devices. It is preferable that the activity identification process be as precise as possible, because of the resource limited feature of a mobile device. So, the research is to use the dataset from the smartphone and use various classification models to find out which classifier is more accurate and provides faster results.