Welcome to the InfoSci Platform
Reference Hub1
Long-Term Synchronization of Hybrid Sensors Networks

Long-Term Synchronization of Hybrid Sensors Networks

Priyanka Madhushri, Emil Jovanov
Copyright: © 2018 |Volume: 9 |Issue: 2 |Pages: 15
ISSN: 1947-3176|EISSN: 1947-3184|EISBN13: 9781522545279|DOI: 10.4018/IJERTCS.2018070103
Cite Article Cite Article

MLA

Madhushri, Priyanka, and Emil Jovanov. "Long-Term Synchronization of Hybrid Sensors Networks." IJERTCS vol.9, no.2 2018: pp.32-46. http://doi.org/10.4018/IJERTCS.2018070103

APA

Madhushri, P. & Jovanov, E. (2018). Long-Term Synchronization of Hybrid Sensors Networks. International Journal of Embedded and Real-Time Communication Systems (IJERTCS), 9(2), 32-46. http://doi.org/10.4018/IJERTCS.2018070103

Chicago

Madhushri, Priyanka, and Emil Jovanov. "Long-Term Synchronization of Hybrid Sensors Networks," International Journal of Embedded and Real-Time Communication Systems (IJERTCS) 9, no.2: 32-46. http://doi.org/10.4018/IJERTCS.2018070103

Export Reference

Mendeley
Favorite Full-Issue Download

Abstract

This article presents synchronization of a hybrid distributed sensor network with wired and wireless sensors. Authors present an implementation of a sleep monitoring system as a hybrid sensor network that combines wireless inertial sensors controlled by a custom smartphone application as an extension of the polysomnographic (PSG) monitor to improve user's comfort. The authors developed an original method of synchronization of wireless sensor data with the PSG records using an auxiliary audio synchronization signal generated by the smartphone. The timestamps on the smartphone are synchronized with the timestamps from inertial sensors, and time of generated synchronization pulses recorded by the PSG. The individual data streams were synchronized using the Dynamic Time Warping (DTW) mechanism. Authors present the system organization and the results of analysis of the whole night monitoring, including the analysis of channel reliability and clock drift. Clock drift has been reduced from 10-30 seconds to 5.1± 3 milliseconds which is with an improved accuracy as compare to existing methods.

Request Access

You do not own this content. Please login to recommend this title to your institution's librarian or purchase it from the IGI Global bookstore.