Abstract
The use of many different types of data sensors makes it possible to better represent and understand a given phenomenon. However, the problem becomes the synchronization and fusion of this data. Our goal was to develop a lightweight and flexible system for synchronized data acquisition from various sensors. We designed the Synchronized Data Acquisition System (SDAS), which uses a self-designed Edge Control Protocol (ECP) and Temporal Sample Alignment (TSA) algorithm to synchronize the acquired samples across all the sensors connected to the SDAS. As samples are synchronized during writing data files, we can call that a software-based synchronization. We also conducted tests to validate our solution.
Paper Type
Poster
DOI
10.62036/ISD.2024.103
Synchronized Data Acquisition System (SDAS) - A Software Approach for Synchronizing Data Recording from Multiple Sensors
The use of many different types of data sensors makes it possible to better represent and understand a given phenomenon. However, the problem becomes the synchronization and fusion of this data. Our goal was to develop a lightweight and flexible system for synchronized data acquisition from various sensors. We designed the Synchronized Data Acquisition System (SDAS), which uses a self-designed Edge Control Protocol (ECP) and Temporal Sample Alignment (TSA) algorithm to synchronize the acquired samples across all the sensors connected to the SDAS. As samples are synchronized during writing data files, we can call that a software-based synchronization. We also conducted tests to validate our solution.
Recommended Citation
Karbowiak, Ł., Piatkowski, J. & Depta, F. (2024). Synchronized Data Acquisition System (SDAS) - A Software Approach for Synchronizing Data Recording from Multiple Sensors. In B. Marcinkowski, A. Przybylek, A. Jarzębowicz, N. Iivari, E. Insfran, M. Lang, H. Linger, & C. Schneider (Eds.), Harnessing Opportunities: Reshaping ISD in the post-COVID-19 and Generative AI Era (ISD2024 Proceedings). Gdańsk, Poland: University of Gdańsk. ISBN: 978-83-972632-0-8. https://doi.org/10.62036/ISD.2024.103