Electronic nose system on the Zynq SoC platform

Amine Ait Si Ali, Hamza Djelouat, Abbes Amira, Faycal Bensaali, Mohieddine Benammar, Amine Bermak

Research output: Contribution to journalArticle

2 Citations (Scopus)

Abstract

Electronic nose or machine olfaction are systems used for detection and identification of odorous compounds and gas mixtures. An electronic nose system is mainly made of two parts, the sensing part which takes the form of a single or a set of sensors and the processing part which takes the form of some pattern recognition algorithms. As an alternative solution to pure software or hardware implementation of the processing part of a gas identification system, this paper proposes a hardware/software co-design approach using the Zynq platform for the implementation of an electronic nose system based on principal component analysis as a dimensionality reduction technique and decision tree as a classification algorithm using two different sensors array, a 4 × 4 in-house fabricated sensor and a commercial one based on 7 Figaro sensors, for comparison purpose. The system was successfully trained and simulated in MATLAB environment prior to the implementation on the Zynq platform. Various scenarios were explored and discussed including the investigation of different combination of principal components as well as the utilization of drift compensation technique to improve the identification accuracy. High level synthesis was carried out on the proposed designs using different optimization directives including loop unrolling, array partitioning and pipelining. Hardware implementation results on the Zynq system on chip show that real-time performances can be achieved for proposed electronic nose systems using hardware/software co-design approach with a single ARM processor running at 667 MHz and the programmable logic running at 142 MHz. In addition, using the designed IP cores and for the best scenarios, a gas can be identified in 3.46 μs using the 4 × 4 sensor and 0.55 μs using the Figaro sensors. Furthermore, it has been noticed that the choice of the sensor array has an important impact on performances in terms of accuracy and processing time. Finally, it has been demonstrated that the programmable logic of the Zynq platform consumes much less power than the processing system.

Original languageEnglish
Pages (from-to)145-156
Number of pages12
JournalMicroprocessors and Microsystems
Volume53
DOIs
Publication statusPublished - 1 Aug 2017

Fingerprint

Sensors
Hardware
Sensor arrays
Processing
ARM processors
Decision trees
Gases
Gas mixtures
Principal component analysis
MATLAB
Pattern recognition
Identification (control systems)
System-on-chip
Electronic nose
Intellectual property core
Compensation and Redress
High level synthesis

ASJC Scopus subject areas

  • Software
  • Hardware and Architecture
  • Computer Networks and Communications
  • Artificial Intelligence

Cite this

Ait Si Ali, A., Djelouat, H., Amira, A., Bensaali, F., Benammar, M., & Bermak, A. (2017). Electronic nose system on the Zynq SoC platform. Microprocessors and Microsystems, 53, 145-156. https://doi.org/10.1016/j.micpro.2017.07.012

Electronic nose system on the Zynq SoC platform. / Ait Si Ali, Amine; Djelouat, Hamza; Amira, Abbes; Bensaali, Faycal; Benammar, Mohieddine; Bermak, Amine.

In: Microprocessors and Microsystems, Vol. 53, 01.08.2017, p. 145-156.

Research output: Contribution to journalArticle

Ait Si Ali, A, Djelouat, H, Amira, A, Bensaali, F, Benammar, M & Bermak, A 2017, 'Electronic nose system on the Zynq SoC platform', Microprocessors and Microsystems, vol. 53, pp. 145-156. https://doi.org/10.1016/j.micpro.2017.07.012
Ait Si Ali, Amine ; Djelouat, Hamza ; Amira, Abbes ; Bensaali, Faycal ; Benammar, Mohieddine ; Bermak, Amine. / Electronic nose system on the Zynq SoC platform. In: Microprocessors and Microsystems. 2017 ; Vol. 53. pp. 145-156.
@article{c4aacac23c4e45008878ca34b0b477ba,
title = "Electronic nose system on the Zynq SoC platform",
abstract = "Electronic nose or machine olfaction are systems used for detection and identification of odorous compounds and gas mixtures. An electronic nose system is mainly made of two parts, the sensing part which takes the form of a single or a set of sensors and the processing part which takes the form of some pattern recognition algorithms. As an alternative solution to pure software or hardware implementation of the processing part of a gas identification system, this paper proposes a hardware/software co-design approach using the Zynq platform for the implementation of an electronic nose system based on principal component analysis as a dimensionality reduction technique and decision tree as a classification algorithm using two different sensors array, a 4 × 4 in-house fabricated sensor and a commercial one based on 7 Figaro sensors, for comparison purpose. The system was successfully trained and simulated in MATLAB environment prior to the implementation on the Zynq platform. Various scenarios were explored and discussed including the investigation of different combination of principal components as well as the utilization of drift compensation technique to improve the identification accuracy. High level synthesis was carried out on the proposed designs using different optimization directives including loop unrolling, array partitioning and pipelining. Hardware implementation results on the Zynq system on chip show that real-time performances can be achieved for proposed electronic nose systems using hardware/software co-design approach with a single ARM processor running at 667 MHz and the programmable logic running at 142 MHz. In addition, using the designed IP cores and for the best scenarios, a gas can be identified in 3.46 μs using the 4 × 4 sensor and 0.55 μs using the Figaro sensors. Furthermore, it has been noticed that the choice of the sensor array has an important impact on performances in terms of accuracy and processing time. Finally, it has been demonstrated that the programmable logic of the Zynq platform consumes much less power than the processing system.",
author = "{Ait Si Ali}, Amine and Hamza Djelouat and Abbes Amira and Faycal Bensaali and Mohieddine Benammar and Amine Bermak",
year = "2017",
month = "8",
day = "1",
doi = "10.1016/j.micpro.2017.07.012",
language = "English",
volume = "53",
pages = "145--156",
journal = "Microprocessors and Microsystems",
issn = "0141-9331",
publisher = "Elsevier",

}

TY - JOUR

T1 - Electronic nose system on the Zynq SoC platform

AU - Ait Si Ali, Amine

AU - Djelouat, Hamza

AU - Amira, Abbes

AU - Bensaali, Faycal

AU - Benammar, Mohieddine

AU - Bermak, Amine

PY - 2017/8/1

Y1 - 2017/8/1

N2 - Electronic nose or machine olfaction are systems used for detection and identification of odorous compounds and gas mixtures. An electronic nose system is mainly made of two parts, the sensing part which takes the form of a single or a set of sensors and the processing part which takes the form of some pattern recognition algorithms. As an alternative solution to pure software or hardware implementation of the processing part of a gas identification system, this paper proposes a hardware/software co-design approach using the Zynq platform for the implementation of an electronic nose system based on principal component analysis as a dimensionality reduction technique and decision tree as a classification algorithm using two different sensors array, a 4 × 4 in-house fabricated sensor and a commercial one based on 7 Figaro sensors, for comparison purpose. The system was successfully trained and simulated in MATLAB environment prior to the implementation on the Zynq platform. Various scenarios were explored and discussed including the investigation of different combination of principal components as well as the utilization of drift compensation technique to improve the identification accuracy. High level synthesis was carried out on the proposed designs using different optimization directives including loop unrolling, array partitioning and pipelining. Hardware implementation results on the Zynq system on chip show that real-time performances can be achieved for proposed electronic nose systems using hardware/software co-design approach with a single ARM processor running at 667 MHz and the programmable logic running at 142 MHz. In addition, using the designed IP cores and for the best scenarios, a gas can be identified in 3.46 μs using the 4 × 4 sensor and 0.55 μs using the Figaro sensors. Furthermore, it has been noticed that the choice of the sensor array has an important impact on performances in terms of accuracy and processing time. Finally, it has been demonstrated that the programmable logic of the Zynq platform consumes much less power than the processing system.

AB - Electronic nose or machine olfaction are systems used for detection and identification of odorous compounds and gas mixtures. An electronic nose system is mainly made of two parts, the sensing part which takes the form of a single or a set of sensors and the processing part which takes the form of some pattern recognition algorithms. As an alternative solution to pure software or hardware implementation of the processing part of a gas identification system, this paper proposes a hardware/software co-design approach using the Zynq platform for the implementation of an electronic nose system based on principal component analysis as a dimensionality reduction technique and decision tree as a classification algorithm using two different sensors array, a 4 × 4 in-house fabricated sensor and a commercial one based on 7 Figaro sensors, for comparison purpose. The system was successfully trained and simulated in MATLAB environment prior to the implementation on the Zynq platform. Various scenarios were explored and discussed including the investigation of different combination of principal components as well as the utilization of drift compensation technique to improve the identification accuracy. High level synthesis was carried out on the proposed designs using different optimization directives including loop unrolling, array partitioning and pipelining. Hardware implementation results on the Zynq system on chip show that real-time performances can be achieved for proposed electronic nose systems using hardware/software co-design approach with a single ARM processor running at 667 MHz and the programmable logic running at 142 MHz. In addition, using the designed IP cores and for the best scenarios, a gas can be identified in 3.46 μs using the 4 × 4 sensor and 0.55 μs using the Figaro sensors. Furthermore, it has been noticed that the choice of the sensor array has an important impact on performances in terms of accuracy and processing time. Finally, it has been demonstrated that the programmable logic of the Zynq platform consumes much less power than the processing system.

UR - http://www.scopus.com/inward/record.url?scp=85026851418&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85026851418&partnerID=8YFLogxK

U2 - 10.1016/j.micpro.2017.07.012

DO - 10.1016/j.micpro.2017.07.012

M3 - Article

AN - SCOPUS:85026851418

VL - 53

SP - 145

EP - 156

JO - Microprocessors and Microsystems

JF - Microprocessors and Microsystems

SN - 0141-9331

ER -