Human Activity Recognition using Accelerometer and Gyroscope Data from Smartphones

Abstract

Human Activity Recognition is a procedure for arranging the activity of an individual utilizing responsive sensors of the smartphone that are influenced by human activity. Its standouts among the most significant building blocks for numerous smartphone applications, for example, medical-related applications, tracking of fitness, context-aware mobile, survey system of human, and so forth. This investigation centers around acknowledgment of human activity utilizing sensors of the smartphone by some machine learning and deep learning characterization approaches. Data received from the accelerometer sensor and gyroscope sensor of the smartphone are grouped to recognize the human activity.