Enhancing real time heavy metal detection using embedded portable signal processing unit
This study presented a low-cost embedded system designed for enhancing Anodic Striping Differential Pulse Voltammetry (ASDPV) signals and detecting heavy metals by implementation of Digital Signal Processing (DSP) unit. For the in-situ analyzing of electrochemical data obtained by ASDPV from a three...
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Medwell Publications
2019
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my.upm.eprints.796982022-10-18T09:01:21Z http://psasir.upm.edu.my/id/eprint/79698/ Enhancing real time heavy metal detection using embedded portable signal processing unit Mazaheri, Amin Mohd Isa, Maryam Mohd Sidek, Roslina Yusof, Nor Azah This study presented a low-cost embedded system designed for enhancing Anodic Striping Differential Pulse Voltammetry (ASDPV) signals and detecting heavy metals by implementation of Digital Signal Processing (DSP) unit. For the in-situ analyzing of electrochemical data obtained by ASDPV from a three-electrode cell. The system implements floating point FIR filter for de-noising of sampled signals for enhancing voltammogram peaks location. On-line multiple peak detection and Gaussian distribution algorithms have been developed onto processor for the detecting and analyzing heavy metals of various applications. Potential scanning range of this device is between - 1500 and + 1500 mV within frequency range 0.1-1 kHz which make the device able to use for measuring wide rang concentrations of samples and environmental monitoring without the need of Personal Computer (PC) or expert user. The developed algorithms has been tested for measuring heavy metal samples with different concentration. Medwell Publications 2019 Article PeerReviewed Mazaheri, Amin and Mohd Isa, Maryam and Mohd Sidek, Roslina and Yusof, Nor Azah (2019) Enhancing real time heavy metal detection using embedded portable signal processing unit. Journal of Engineering and Applied Sciences, 14 (18). pp. 6650-6658. ISSN 1816-949X; ESSN: 1818-7803 https://medwelljournals.com/abstract/?doi=jeasci.2019.6650.6658 10.36478/jeasci.2019.6650.6658 |
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This study presented a low-cost embedded system designed for enhancing Anodic Striping Differential Pulse Voltammetry (ASDPV) signals and detecting heavy metals by implementation of Digital Signal Processing (DSP) unit. For the in-situ analyzing of electrochemical data obtained by ASDPV from a three-electrode cell. The system implements floating point FIR filter for de-noising of sampled signals for enhancing voltammogram peaks location. On-line multiple peak detection and Gaussian distribution algorithms have been developed onto processor for the detecting and analyzing heavy metals of various applications. Potential scanning range of this device is between - 1500 and + 1500 mV within frequency range 0.1-1 kHz which make the device able to use for measuring wide rang concentrations of samples and environmental monitoring without the need of Personal Computer (PC) or expert user. The developed algorithms has been tested for measuring heavy metal samples with different concentration. |
format |
Article |
author |
Mazaheri, Amin Mohd Isa, Maryam Mohd Sidek, Roslina Yusof, Nor Azah |
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Mazaheri, Amin Mohd Isa, Maryam Mohd Sidek, Roslina Yusof, Nor Azah Enhancing real time heavy metal detection using embedded portable signal processing unit |
author_facet |
Mazaheri, Amin Mohd Isa, Maryam Mohd Sidek, Roslina Yusof, Nor Azah |
author_sort |
Mazaheri, Amin |
title |
Enhancing real time heavy metal detection using embedded portable signal processing unit |
title_short |
Enhancing real time heavy metal detection using embedded portable signal processing unit |
title_full |
Enhancing real time heavy metal detection using embedded portable signal processing unit |
title_fullStr |
Enhancing real time heavy metal detection using embedded portable signal processing unit |
title_full_unstemmed |
Enhancing real time heavy metal detection using embedded portable signal processing unit |
title_sort |
enhancing real time heavy metal detection using embedded portable signal processing unit |
publisher |
Medwell Publications |
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2019 |
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http://psasir.upm.edu.my/id/eprint/79698/ https://medwelljournals.com/abstract/?doi=jeasci.2019.6650.6658 |
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