New Trends and Problems in Sensors Arrays Applications

Chemical imaging and in particular olfactory imaging is becoming a powerful tool for the analysis of complex chemical environments. This work is aimed at describing trends, problems and possible solution in the frame of multicomponent analysis applied to sensors arrays which are employed for the environment characterization from the quantitative and qualitative points of view. In particular comments are given on the possiblity of improving sensors arrays performances through both a better material quality control of the single sensing element and a deeper attention to noise matching conditions for getting a better resolution. A number of data analysis methods can be utilized to process sensors arrays data, among them self organized neural networks have been proven to provide substantial improvements. One of the most important feature of the olfaction of the mammalians is its non statical behaviour. The dynamics of the olfactory bulb (which is the neuronal structure incharged to preprocess the olfactory receptors signals) seems to play a fundamental role in odour recognition. From this consideration a number of new data analysis methods can arise providing a substantial improvement to sensors arrays applications.