Fast Fourier Transform of non-periodic signals generated from a microplasma: migrating from a desktop computer to an IoT-connected smartphone

Ryan Fitzgerald; Emily Wang; Vassili Karanassios

doi:10.1117/12.2305462

14 May 2018 Fast Fourier Transform of non-periodic signals generated from a microplasma: migrating from a desktop computer to an IoT-connected smartphone

Ryan Fitzgerald, Emily Wang, Vassili Karanassios

Author Affiliations +

Proceedings Volume 10657, Next-Generation Spectroscopic Technologies XI; 1065703 (2018) https://doi.org/10.1117/12.2305462
Event: SPIE Commercial + Scientific Sensing and Imaging, 2018, Orlando, FL, United States

Abstract

There are many applications requiring an instrument to be brought to the sample for chemical analysis onsite (rather than bringing a sample to a lab for analysis, as is done traditionally). Ideally, for such applications, a portable chemical analysis instrument must be capable of acquiring data using a smartphone, have wireless capability and it must be able to become part of the Internet-of-Things (IoT). But do smartphones have the required processing power to execute computationally-intensive algorithms, such as a Fast Fourier Transform (FFT)? Among others, FFTs are used for filtering (e.g., de-noising) of periodic signals, thus improving Signal-to-Noise Ratio (SNR). Using non-periodic signals and Fourier-domain interpolation for resolution enhancement, it will be shown that smartphones do have the necessary power.

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Ryan Fitzgerald, Emily Wang, and Vassili Karanassios "Fast Fourier Transform of non-periodic signals generated from a microplasma: migrating from a desktop computer to an IoT-connected smartphone", Proc. SPIE 10657, Next-Generation Spectroscopic Technologies XI, 1065703 (14 May 2018); https://doi.org/10.1117/12.2305462

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