A gas discrimination system is mainly made of two parts, the sensing part and the processing part. As an alternative solution to pure software or hardware implementation of the processing part of a gas identification system, this paper proposes a gas discrimination system and its implementation on the Zynq system on chip platform using hardware/software co-design approach. In addition, the recommended system uses principal component analysis for dimensionality reduction, binary decision tree for classification and a 4×4 in-house gas sensor array for sensing. Moreover, k-nearest neighbors classifier is also used and compared with decision tree. MATLAB is used for simulation and validation before the final implementation on the Zynq. Algorithms are implemented using high level synthesis and different optimization directives are applied. Hardware implementation results on the Zynq show that real-time performances can be achieved for proposed e-nose system using hardware/software co-design approach with a single ARM processor running at 667 MHz and the programmable logic running at 142 MHz.
|Title of host publication||2016 IEEE 27th International Conference on Application-Specific Systems, Architectures and Processors, ASAP 2016|
|Number of pages||2|
|Publication status||Published - 28 Nov 2016|
|Event||27th IEEE International Conference on Application-Specific Systems, Architectures and Processors, ASAP 2016 - London, United Kingdom|
Duration: 6 Jul 2016 → 8 Jul 2016
|Conference||27th IEEE International Conference on Application-Specific Systems, Architectures and Processors, ASAP 2016|
|Period||6/07/16 → 8/07/16|