@inproceedings{b487c021721d41a5a2d5f97a9b906503,
title = "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.",
keywords = "Accelerometer, Classification, Gyroscope, Human Activity Recognition, Machine Learning, Smartphone",
author = "Khimraj and Shukla, {Praveen Kumar} and Ankit Vijayvargiya and Rajesh Kumar",
note = "Publisher Copyright: {\textcopyright} 2020 IEEE.; 2020 IEEE International Conference on Emerging Trends in Communication, Control and Computing, ICONC3 2020 ; Conference date: 21-02-2020 Through 22-02-2020",
year = "2020",
month = feb,
doi = "10.1109/ICONC345789.2020.9117456",
language = "English",
series = "Proceedings - 2020 International Conference on Emerging Trends in Communication, Control and Computing, ICONC3 2020",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "Proceedings - 2020 International Conference on Emerging Trends in Communication, Control and Computing, ICONC3 2020",
address = "United States",
}