Embedded Platform for Gas Applications Using Hardware/Software Co-Design and RFID
المؤلف | Ali A.A.S. |
المؤلف | Farhat A. |
المؤلف | Mohamad S. |
المؤلف | Amira A. |
المؤلف | Bensaali F. |
المؤلف | Benammar M. |
المؤلف | Bermak A. |
تاريخ الإتاحة | 2019-09-30T07:47:43Z |
تاريخ النشر | 2018 |
اسم المنشور | IEEE Sensors Journal |
المصدر | Scopus |
الرقم المعياري الدولي للكتاب | 1530-437X |
الملخص | 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 and 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 SnO 2 based sensor and seven 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 (C 2 H 6 O), carbon dioxide (CO 2 ), propane (C 3 H 8 ), ammonia (NH 3 ), and hydrogen (H 2 ). 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. |
راعي المشروع | Manuscript received December 25, 2017; revised March 17, 2018; accepted March 18, 2018. Date of publication April 3, 2018; date of current version May 9, 2018. This paper was supported by the National Priorities Research Program under Grant 5-080-2-028 from the Qatar National Research Fund (a member of Qatar Foundation). The associate editor coordinating the review of this paper and approving it for publication was Prof. Mehmet Yuce. (Corresponding author: Ali Farhat.) A. Ait Si Ali is with the Faculty of Engineering and Environment, University of Northumbria, Newcastle upon Tyne NE1 8ST, U.K. (e-mail: amine.ali@northumbria.ac.uk). |
اللغة | en |
الناشر | Institute of Electrical and Electronics Engineers Inc. |
الموضوع | E-Nose gas sensing real-time processing RFID tag temperature sensing Zynq SoC |
النوع | Article |
الصفحات | 4633-4642 |
رقم العدد | 11 |
رقم المجلد | 18 |
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