Human Activity Recognition using Smartphones

Abstract

Activity recognition is one of the most important technologies behind various
applications such as medical science, human survey system and it is an influential research
subject in health care and smart homes. Human Activity Recognition(HAR) classifies a person's
behavior using sensitive sensors that are influenced by human movement. Both users and mobile
capabilities (sensors) are growing and users typically bring their mobile with them. These facts
make HAR bigger and more famous. This research focuses on the identification of human
behavior using smartphone sensors that use different approaches to classifying machine learning.
To identify human activity, data obtained from the accelerometer and gyroscope sensors of smart
phones are classified.