Human-Activity-Recognition

Human Activity Recognition Using Smartphones Data Set

Abstract-

In this project, we calculate a model by which a smartphone can detect its owner’s activity precisely. For the dataset, 30 people were used to perform 6 different activities. Each of them was wearing a Samsung Galaxy SII on their waist. Using the smartphone’s embedded sensors (the accelerometer and the gyroscope), the user’s speed and acceleration were measured in 3-axial directions. We use the sensor’s data to predict user’s activity. After preparing the datasets and doing some machine learning methods.