Human Activity Recognition : Models Using Limited Consumer Device Sensors and Machine Learning Aims Research

Abstract

Human activity recognition has grown in popularity significantly with daily lifestyle or medical related applications. Data collection is limited to easily accessible devices: smartphones and smartwatches. Eliminate the need for specialized but less accessible data recording instruments. Presentation of findings of different models that are limited to training using such sensors.