Using Smartphone Accelerometer for Human Physical Activity and Context Recognition in-the-Wild

摘要

Adaptation of smart devices is frequently rising, where a new generation of smartphones is growing into an emerging platform for personal computing, monitoring, and private data processing. Smartphone sensing allows collecting data from immediate environments and surroundings to recognize human daily living activities and behavioral contexts. Although smartphone-based activity recognition is universal; however, there is a need for coinciding recognition of in-the-wild human physical activities and the associated contexts. This research work proposes a two-level scheme for in-the-wild recognition of human physical activities and the corresponding contexts based on the smartphone accelerometer data. Different classifiers are used for experimentation purposes, and the achieved results validate the efficiency of the proposed scheme.