Towards Flooring Material Classification Using Acoustic Signal from COTS Mobile Devices

Abstract

Amongst densely populated areas such as New York, Hong Kong, Seoul and etc., apartments and condominiums grew to be the most commonly used type of housing units. Throughout the years we have witnessed many issues within the residents living in such units suffer from apartment noise. Lousy neighbors are not the only cause of such problems but the way houses were built, more specifically type and thickness of the flooring materials, determines the amount of noise transfer from one household to the other. In this paper, we show feasibility of classifying flooring materials using COTS (Commercial Off-The-Shelf) mobile devices. We exert each flooring materials propagating synthetic chirps in various ways. Our approach makes it possible to distinguish three types of target flooring materials (wood, polystyrene and concrete) and can also give similar results when the target materials are piled on top of one another. To this end we i) design an acoustic signal which effectively differentiates each target flooring materials, ii) gather sound samples propagated from the target materials, and iii) provide a classification methodology using methods such as SVM and KNN. Finally, we discuss the necessities to achieve the final goal of identifying flooring materials and their thickness.