Electronic nose system on the Zynq SoC platform

Abstract

Electronic nose or machine olfaction are systems used for detection and identification of odorous com- pounds 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 pat- tern 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 ap- proach 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 algo- rithm 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 MAT- LAB 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 uti- lization 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, ar- ray 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 run- ning at 142 MHz. In addition, using the designed IP cores and for the best scenarios, a gas can be iden- tified 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 ac- curacy and processing time. Finally, it has been demonstrated that the programmable logic of the Zynq platform consumes much less power than the processing system.