Applications and Technology of Electronic Nose

Project Member(s): Su, S.

Funding or Partner Organisation: Commonwealth Scientific and Industrial Research Organisation (CSIRO Scholarships)
Commonwealth Scientific and Industrial Research Organisation (CSIRO Scholarships)

Start year: 2017

Publications:

Zhang, S, Lin, M, Zou, X, Su, S, Zhang, W, Zhang, X & Guo, Z 2020, 'LSTM-based air quality predicted model for large cities in China', Nature Environment and Pollution Technology, vol. 19, no. 1, pp. 229-236.

Liu, T, Zhang, W, McLean, P, Ueland, M, Forbes, SL & Su, SW 2018, 'Electronic Nose-Based Odor Classification using Genetic Algorithms and Fuzzy Support Vector Machines', International Journal of Fuzzy Systems, vol. 20, no. 4, pp. 1309-1320.
View/Download from: Publisher's site

Zhang, W, Liu, T, Zhang, M, Zhang, Y, Li, H, Ueland, M, Forbes, SL, Rosalind Wang, X & Su, SW 1970, 'NOS.E: A New Fast Response Electronic Nose Health Monitoring System', 2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), IEEE, USA, pp. 4977-4980.
View/Download from: Publisher's site

FOR Codes: Air Quality, Electrical and Electronic Engineering, Electronic sensors, Air quality, atmosphere and weather

Acknowledgement of Country

UTS acknowledges the Gadigal people of the Eora Nation, the Boorooberongal people of the Dharug Nation, the Bidiagal people and the Gamaygal people, upon whose ancestral lands our university stands. We would also like to pay respect to the Elders both past and present, acknowledging them as the traditional custodians of knowledge for these lands.