Identification and quantification of mixed air pollutants based on homotopy method for gas sensor array

Accurate recognition of air pollutants and estimation of their concentrations are critical for human health and safety monitoring and can be achieved using gas sensor arrays. In this paper, an efficient method based on a homotopy algorithm is presented for the analysis of sensor arrays responding to binary mixtures. The new method models the responses of a gas sensor array as a system of nonlinear equations and provides a globally convergent way to find the solution of the system. Real data measurement for CH₄ and SO₂ are used to model sensor responses. The model is applied to the method for prediction and it shows the prediction results are within 1% variation of true values for both gas models.