Environmental monitoring relies on compact, portable sensor systems capable of detecting pollutants in real-time. An integrated chemical sensor array system is developed for detection and identification of environmental pollutants in diesel and gasoline exhaust fumes. The system consists of a low noise floor analog front-end (AFE) followed by a signal processing stage. In this paper, we present techniques to detect, digitize, denoise and classify a certain set of analytes. The proposed AFE reads out the output of eight conductometric sensors and eight amperometric electrochemical sensors and achieves 91 dB SNR at 23.4 mW quiescent power consumption for all channels. We demonstrate signal denoising using a discrete wavelet transform based technique. Appropriate features are extracted from sensor data, and pattern classification methods are used to identify the analytes. Several existing pattern classification algorithms are used for analyte detection and the comparative results are presented.
This is a preview of subscription content, access via your institution.
Buy single article
Instant access to the full article PDF.
Price excludes VAT (USA)
Tax calculation will be finalised during checkout.
Reed, M. D., et al. (2008). Health effects of subchronic inhalation exposure to gasoline engine exhaust. Inhalation Toxicology, 20(13), 1125–1143.
U.S. EPA. (2002). Health assessment document for diesel engine exhaust (Final 2002). U.S. Environmental Protection Agency, Office of Research and Development, National Center for Environmental Assessment, Washington Office, Washington, DC, EPA/600/8-90/057F.
Sydbom, A., et al. (2001). Health effects of diesel exhaust emissions. European Respiratory Journal, 17, 733–746.
Bhatia, R., Lopipero, P., & Smith, A. H. (1998). Diesel exhaust exposure and lung cancer. Epidermology, 9(1), 84–91.
Office of population genomics. Available online at http://www.genome.gov/.
Scott, S. M., James, D., & Ali, Z. (2007). Data analysis for electronic nose systems. Microchimica Acta, 156(3–4), 183–207.
Gardner J. W., & Bartlett P. N. (1999). Electronic noses: Principles and applications. Oxford University Press, USA.
Olafsdottir, G., Jonsdottir, R., Lauzon, H. L., Luten, J. B., & Kristbergsson, K. (2005). Characterization of volatile compounds in chilled cod (Gadus morhua) fillets by gas chromatography and detection of quality indicators by an electronic nose. Journal of Agricultural and Food Chemistry, 53(26), 10140–10147.
Marina, S., et al. (2007). Use of a MS-electronic nose for prediction of early fungal spoilage of bakery products. International Journal of Food Microbiology, 114(1), 10–16.
Di Natale, C., et al. (1999). Electronic nose analysis of urine samples containing blood. Physiological Measurement, 20, 377–384.
Shykhon, M. E., Morgan, D. W., Dutta, R., Hines, E. L., & Gardner, J. W. (2004). Clinical evaluation of the electronic nose in the diagnosis of ear, nose and throat infection: a preliminary study. Journal of Laryngology and Otology, 118, 706–709.
Engin, G. (1997). Characterization of sewage and sewage odors by using an electronic nose. Master’s Thesis, Department of Civil Engineering, University of Hertfordshire, U.K.
Rock, F., Barsan, N., & Weimar, U. (2008). Electronic nose: Current status and future trends. Chemical Reviews, 108(2), 705–725.
Zhou, H., Homer, M. L., Shevade, A. V., & Ryan, M. A. (2006). Nonlinear least-squares based method for identifying and quantifying single and mixed contaminants in air with an electronic nose. IEEE Sensors Journal, 6, 1–18.
Blaschke, M., et al. (2006). MEMS gas-sensor array for monitoring the perceived car-cabin air quality. IEEE Sensors Journal, 6(5), 1298–1308.
Nicolas, J., Romain, A. C., & Ledent, C. R. (2006). The electronic nose as a warning device of the odour emergence in a compost hall. Sensors and Actuators B, 116(1–2), 95–99.
Mulchandani, A., Myung, N. V., Deshusses, M. A., Cocker, D., Wang, J., Bakkaloglu, B., et al. (2008). Nanosensor array for real-time monitoring of diesel and gasoline exhaust exposure. Epidemiology, 19(6), S62.
Konnanath, B., Kim, H., Spanias, A., Bakkaloglu, B., Wang, J., Mulchandani, A., & Myung, N. (2009). A real-time monitoring system for diesel and gasoline exhaust exposure. In Proceedings of the IEEE 16th International Conference on DSP, pp. 1–5, Jul 2009.
Wang, J. (1985). Stripping analysis: Principles, instrumentation, and applications. VCH: Deerfield Beach.
Martin, S. M., Gebara, F. H., Strong, T. D., & Brown, R. B. (2004). A low-voltage chemical sensor interface for systems-on-chip: The fully-differential potentiostat. In Proceedings of the IEEE International Symposium on Circuits and Systems, vol. 4, pp. 892–895.
Castello, R., & Gray, P. R. (1985). A high-performance micropower switched-capacitor filters. The IEEE Journal of Solid-State Circuits, SC-20(6), 1122–1132.
Zhang, T., Mubeen, S., Myung, N., & Deshusses, M. A. (2008). Recent progress in carbon nanaotube-based gas sensor. Nanotechnology, IOP, pp. 1–14.
Bakker, A., Thiele, K., & Huijsing, J. H. (2000). A CMOS nested-chopper instrumentation amplifier with 100-nV offset. The IEEE Journal of Solid-State Circuits, 35(12), 1877–1883.
Wonseok Oh, Bakkaloglu, B., Wang, C., & Hoon, S. K. (2008). A CMOS low noise, chopper stabilized low-dropout regulator with current-mode feedback error amplifier. IEEE Transactions on Circuits and Systems, 55(10), Nov 2008.
Wang, J. (1996). Electrochemical transduction. In R. F. Taylor & J. S. Schultz (Eds.), Handbook of chemical and biological sensors (pp. 123–137). Bristol, UK: IOP Publishing.
Donoho, D. L. (1995). De-noising by soft thresholding. IEEE Transactions on Information Theory, 41(3), 613–627.
Jagtiani, A. V., Sawant, R., Carletta, J., & Zhe, J. (2008). Wavelet transform-based methods for denoising of Coulter counter signals. Measurement Science and Technology, 19(6), 1–15.
Deshusses, M. (2008). Dataset-S: Synthetic dataset, Department of Chemical and Environmental Engineering. University of California-Riverside.
Duda, R. O. (2006). Pattern recognition for machine learning. Berlin: Springer.
Gardner, J. W., Shin, H. W., Hines, E. L., & Dow, C. S. (2000). An electronic nose system for monitoring the quality of potable water. Sensors and Actuators B, 69(3), 336–341.
Barko, G., & Hlavay, J. (2000). Application of principal component analysis for the characterization of a piezoelectric sensors array. Analytica Chimica Acta, 367(1–3), 135–143.
Ripley, B. D. (1996). Pattern recognition and neural networks. Cambridge: Cambridge University Press.
Duda, R. O., Hart, P. E., & Stork, D. G. (2001). Pattern classification. New York: Wiley.
Discriminant analysis toolbox. Available online at http://www.mathworks.com/matlabcentral/fileexchange/authors/1714.
Haykin, S. (1999). Neural networks: A comprehensive foundation. New Jersey: Prentice Hall.
Netlab neural network software. Available online at http://www.ncrg.aston.ac.uk/netlab/index.php.
The Spider version 1.71 for MATLAB. Available online at http://www.kyb.mpg.de/bs/people/spider/main.html.
Mulchandani, A. et al. (2009). Dataset-E1: Experimental dataset, Department of Chemical and Environmental Engineering, University of California-Riverside.
Mulchandani, A. et al. (2009). Dataset-E2: Experimental dataset, Department of Chemical and Environmental Engineering, University of California-Riverside.
Wang, J., et al. (2009). Dataset E3: Experimental dataset. University of California-San Diego: Laboratory for Nanobioelectronics.
Wang, J., et al. (2008). Dataset T1: Experimental dataset, Center for Bioelectronics and Biosensors, Arizona State University.
Wang, J., et al. (2008). Dataset T2: Experimental dataset, Laboratory for Nanobioelectronics. San Diego: University of California.
Haddad, R., Carmel, L., & Harel, D. (2007). A feature extraction algorithm for multi-peak signals in electronic noses. Sensors and Actuators B, 120(2), 467–472.
Bard, A. J., & Raulkner, L. R. (2001). Electrochemical methods: Fundamentals and applications. New York: Wiley.
Levine, P. M., Gong, P., Levicky, R., & Shepard, K. L. (2008). Active CMOS sensor array for electrochemical biomolecular detection. The IEEE Journal of Solid-State Circuits, 43(8), 1859–1871.
Malcovati, P., Brigati, S., Francesconi, F., Maloberti, F., Cusinato, P., & Baschirotto, A. (2003). Behavioral modeling of switched-capacitor sigma-delta modulators. IEEE Transactions on Circuit and System, 50(3), 352–364.
Schreier, R., & Temes, G. C. (2005). Understanding delta-sigma data converters. Hoboken, NJ: IEEE Press, Wiley-Interscience.
Martin, S. M., Gebara, F. H., Larivee, B. J., & Brown, R. B. (2004). A CMOS integrated microintrument for trace detection of heavy metals. In Proceedings of the IEEE International Symposium on Circuits and Systems, vol. 4, pp. 892–895.
This work was supported through the NIH Genes, Environment and Health Initiative through award 3U01ES016026-02S1.
About this article
Cite this article
Kim, H., Konnanath, B., Sattigeri, P. et al. Electronic-nose for detecting environmental pollutants: signal processing and analog front-end design. Analog Integr Circ Sig Process 70, 15–32 (2012). https://doi.org/10.1007/s10470-011-9638-1