Embedded Platform for Gas Applications Using Hardware/Software Co-Design and RFID

Ait Si Ali, Amine, Farhat, Ali, Mohamad, Saqib, Amira, Abbes, Bensaali, Faycal, Benammar, Mohieddine and Bermak, Amine (2018) Embedded Platform for Gas Applications Using Hardware/Software Co-Design and RFID. IEEE Sensors Journal. ISSN 1530-437X (In Press)

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Official URL: https://doi.org/10.1109/JSEN.2018.2822711

Abstract

This paper presents the development of a wireless low power reconfigurable self-calibrated multi-sensing platform for gas sensing applications. The proposed electronic nose (EN) system monitors gas temperatures, concentrations and mixtures wirelessly using the radio-frequency identification (RFID) technology. The EN takes the form of a set of gas and temperature sensors as well as multiple pattern recognition algorithms implemented on the Zynq system on chip (SoC) platform. The gas and temperature sensors are integrated on a semi-passive RFID tag to reduce the consumed power. Various gas sensors are tested including an in-house fabricated 4×4 SnO2 based sensor and 7 commercial Figaro sensors. The Data is transmitted to the Zynq based processing unit using a RFID reader where it is processed using multiple pattern recognition algorithms for dimensionality reduction and classification. Multiple algorithms are explored for optimum performance including principal component analysis (PCA) and linear discriminant analysis (LDA) for dimensionality reduction while decision tree (DT) and k-nearest neighbors (KNN) are assessed for classification purpose. Different gases are targeted at diverse concentration including carbon monoxide (CO), ethanol (C2H6O), carbon dioxide (CO2), propane (C3H8), ammonia (NH3) and hydrogen (H2). An accuracy of 100% is achieved in many cases with an overall accuracy above 90% in most scenarios. Finally, the hardware/software heterogeneous solution to implementation PCA, LDA, DT and KNN on the Zynq SoC shows promising results in terms of resources usage, power consumption and processing time.

Item Type: Article
Uncontrolled Keywords: RFID Tag, Zynq SoC, E-Nose, Real-time Processing, Gas Sensing, Temperature Sensing
Subjects: G400 Computer Science
G700 Artificial Intelligence
H600 Electronic and Electrical Engineering
Department: Faculties > Engineering and Environment > Computer and Information Sciences
Depositing User: Amine Ait Si Ali
Date Deposited: 11 Apr 2018 10:16
Last Modified: 11 Apr 2018 11:11
URI: http://nrl.northumbria.ac.uk/id/eprint/33914

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