In this paper a new technology, based on HyperSpectral Imaging (HSI) sensors, and related detection architectures, is
investigated in order to develop suitable and low cost strategies addressed to: i) preliminary detection and
characterization of the composition of the structure to dismantle and ii) definition and implementation of innovative
smart detection engines for sorting and/or demolition waste flow stream quality control. The proposed sensing
architecture is fast, accurate, affordable and it can strongly contribute to bring down the economic threshold above which
recycling is cost efficient. Investigations have been carried out utilizing an HSI device working in the range 1000-1700
nm: NIR Spectral Camera™, embedding an ImSpector™ N17E (SPECIM Ltd, Finland). Spectral data analysis was
carried out utilizing the PLS_Toolbox (Version 6.5.1, Eigenvector Research, Inc.) running inside Matlab® (Version
7.11.1, The Mathworks, Inc.), applying different chemometric techniques, selected depending on the materials under
investigation. The developed procedure allows assessing the characteristics, in terms of materials identification, such as
recycled aggregates and related contaminants, as resulting from end-of-life concrete processing. A good classification of
the different classes of material was obtained, being the model able to distinguish aggregates from other materials (i.e.
glass, plastic, tiles, paper, cardboard, wood, brick, gypsum, etc.).