Abstract
Industrial odor concentration measurement in continuous mode is a challenging task using olfactometers, as it's expensive and requires human involvement for a prolonged time. This chapter presents the development of an indigenous metal oxide sensor-based electronic nose system for measurement of industrial odor in ou/m3. The results of electronic nose and field olfactometer were correlated using multilinear regression and partial least square regression techniques. The results showed satisfactory prediction by both the models, with RMSE (6.70, and 4.02), RAE (0.29 and 0.16), and NAE (0.89 and 0.96), respectively, for MLR and PLS. The results indicated better performance of PLS compared to MLR. The objective of the present work is to train and employ artificial olfaction system for continuous measurement of obnoxious emissions emitted from industries bypassing involvement of olfactometer.
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