Citazione: Vincenzo Di Lecce, Marco Calabrese, Rita Dario, Computational-based Volatile Organic Compounds discrimination: an experimental low-cost setup, Proc. of the 2010 IEEE International Conference on Computational Intelligence for Measurement Systems and Applications Taranto (CIMSA2010), Italy, 6-8 September 2010, pp. 54-59, ISBN: 978-1-4244-7229-1
Abstract: In this work, an array of low-cost cross-sensitive sensors is used in the search for the best candidate within a set of volatile organic compounds (VOCs). The challenge of our experimental setting is to partially surmount the problems of low selectivity, especially in normal operating conditions, so that ambiguous sensor responses (i.e. referable to more than one VOC) are interpreted properly. In order to carry out the signal disambiguation task, a computational technique employing simple classification rules and fuzzy descriptions has been engineered. The basic idea is that, if the same gas is actually measured by two or more sensors, then the estimated concentrations will show a low variance, with an accuracy depending on the number of concordant sensors. Experiments show that, despite the cheapness of the setup, encouraging results can be obtained.
Keyword: low-cost sensors; sensor array; sensor response disambiguation; fuzzy descriptions