Open AccessHuman Movement Monitoring Simulation Using an IoT-based self-powered TENG Intelligent Chair
Author(s) -
Mohammed Hussein Ahmed Alanesi,
Daoguo Yang
Publication year - 2022
Publication title -
international journal for research in applied science and engineering technology
Language(s) - English
Resource type - Journals
ISSN - 2321-9653
DOI - 10.22214/ijraset.2022.40957
Subject(s) - movement (music) , computer science , triboelectric effect , nanogenerator , internet of things , sitting , artificial intelligence , electrical engineering , voltage , engineering , embedded system , acoustics , physics , medicine , pathology , quantum mechanics
The internet has had a profound effect on human life. Since each individual has distinct movement characteristics, monitoring human motion can enable identity recognition. This paper describes the development of a self-powered triboelectric nanogenerator (TENG) band's array for recognizing students' identities in the classroom by collecting movement information derived from electric signals during sitting, standing, turning left and right while sitting, and breathing on the chair. The band's array is soft, stretchy, and cheap, constructed of a rubber tube filled with locally created physiological saline. It can be mounted on the intelligent chair in two positions: seat and backrest. Furthermore, utilizing MATLAB software and a specialized algorithm, the band's array can identify and authenticate students' identification in real-time with an ERR of 19.6 %. Keywords: Intelligent chair; self-powered Triboelectric Nanogenerator; Internet of Things; student motion detection; Identity recognition