Hyperspectral imaging applied to end-of-life (EOL) concrete recycling

Bonifazi, Giuseppe; Palmieri, Roberta; Serranti, Silvia

doi:10.1515/teme-2015-0044

Cited by 16 publications

(7 citation statements)

References 10 publications

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“…This ability has opened the way of using spectra as surrogate markers of complex attributes of organic structures, which can be studied and classified with the application of specific statistical packages, without the need for chemical information from the analysis of molecular bonds in the NIR spectrum. At present, this application of NIR spectroscopy is used to perform systematic environmental remote and proximal sensing 15 , specifically in the primary/secondary raw materials sector [16][17][18] , cultural heritage 19,20 , the agricultural/food industry [21][22][23] , the pharmaceutical and chemical industry 24,25 , and analytical science 26 .…”

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confidence: 99%

Near infrared spectroscopy as a tool for in vivo analysis of human muscles

Bonifazi

Cardillo

Currà

et al. 2018

Smart Biomedical and Physiological Sensor Technology XV

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Recent advances in materials and fabrication techniques provided portable, performant, sensing optical spectrometers readily operated by user-friendly cabled or wireless systems. such systems allow rapid, non-invasive, and not destructive quantitative analysis of human tissues. This proof-ofprinciple investigation tested whether infrared spectroscopy techniques, currently utilized in a variety of areas, could be applied in living humans to categorize muscles. Using an ASD FieldSpec® 4 Standard-Res Spectroradiometer with a spectral sampling capability of 1.4 nm at 350-1000 nm and 1.1 nm at 1001-2500 nm, we acquired reflectance spectra in visible shortwave infra-red regions (350-2500 nm) from the upper limb muscles (flexors and extensors) of 20 healthy subjects (age 25-89 years, 9 women). Spectra off-line analysis included preliminary preprocessing, Principal Component Analysis, and Partial Least-Squares Discriminant Analysis. Near-infrared (NIR) spectroscopy proved valuable for noninvasive assessment of tissue optical properties in vivo. In addition to the non-invasive detection of tissue oxygenation, NIR spectroscopy provided the spectral signatures (ie, "fingerprints") of upper limb flexors and extensors, which represent specific, accurate, and reproducible measures of the overall biological status of these muscles. Thus, non-invasive NIR spectroscopy enables more thorough evaluation of the muscular system and optimal monitoring of the effectiveness of therapeutic or rehabilitative interventions.

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confidence: 99%

Near infrared spectroscopy as a tool for in vivo analysis of human muscles

Bonifazi

Cardillo

Currà

et al. 2018

Smart Biomedical and Physiological Sensor Technology XV

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“…This study aimed to define a method based on Hyperspectral Imaging (HSI) [7][8][9][10][11] to automatically detect and identify contaminants like plastic, wood and drywall in a post-earthquake building waste flow stream. To reach this goal HSI *silvia.serranti@uniroma1.it; phone 39 6 44585 360; fax 39 06 44585 618; www.uniroma1.it data were used in the Short-Wave InfraRed (SWIR) range (1000-2500 nm), applying different chemometric methods, like principal component analysis for data exploration and partial least-square-discriminant analysis to build classification models.…”

Section: Introductionmentioning

confidence: 99%

An innovative approach based on hyperspectral imaging for an automatic characterization of post-earthquake building waste

Bonifazi¹,

Capobianco²,

Serranti³

et al. 2023

Photonic Instrumentation Engineering X

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The construction sector produces more than one-third of the world's solid waste. Construction and demolition waste (CDWs) are generated from the construction, renovation and demolition of buildings, roads, bridges and other structures. Moreover, CDW include the materials that may suddenly be generated by natural disasters, such as earthquakes and floods. Post-earthquake building waste (PBW) is typically composed of a mixture of different materials, such as concrete, bricks, tiles, ceramics, wood, glass, gypsum and plastic. These materials represent, if properly separated, a high potential for recycling and reuse particularly the inert fraction, representing about 70% of the total. From this perspective, this work aims to develop an innovative strategy based on optical sensing in order to identify and classify different types of PBW coming from a post-earthquake site (Amatrice, Italy). A strategy based on hyperspectral imaging (HSI) working in the SWIR range (1000-2500 nm) was developed. The acquired hyperspectral images were analyzed using different chemometric methods: principal component analysis (PCA) for data exploration and partial least-squarediscriminant analysis (PLSDA) to build a classification model. Results showed that the proposed approach allows to recognize and classify inert fractions from contaminants (i.e., wood, plastics and drywall). The obtained results show how HSI could be particularly suitable to perform classification in complex scenarios as produced by earthquakes.

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“…2003), and more generally in analytical science (Pasquini, 2003). In recent decades, HSI has emerged in the recycling sector (Bonifazi et Al. 2015b;Serranti et Al.…”

Section: Introductionmentioning

confidence: 99%

Detecting Contaminants in Post-Consumer Plastic Packaging Waste by a Nir Hyperspectral Imaging-Based Cascade Detection Approach

2021

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Recycling of post-consumer packaging wastes involves a complex chain of activities, usually based on three main stages, that is: i) collection from households or recovery from Municipal solid waste (MSW), ii) sorting and, finally, iii) mechanical recycling. The systematic identification of impurities inside plastic packaging waste streams, and the assessment of the different occurring materials, can be considered as one of the key issues to certify and to classify waste materials fed to recycling plants and to perform a full control of the resulting processed fractions and byproducts, that have to comply with market demands. The utilization of a Near InfraRed (NIR) – HyperSpectral Imaging (HSI) based methods, along with chemometrics and machine learning techniques, can fulfill these goals. In this paper, the HSI-based sorting logics, to apply, to implement and to set up to perform an automatic separation of paper, cardboard, plastics and multilayer packaging are investigated.

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Hyperspectral imaging applied to end-of-life (EOL) concrete recycling

Abstract: The recovery of materials from DW is an important target of the recycling industry and it is important to know which materials are present in order to set up efficient sorting and/or quality control actions. The implementation of an automatic recognition system of recovered products from

Cited by 16 publications

References 10 publications

Near infrared spectroscopy as a tool for in vivo analysis of human muscles

Near infrared spectroscopy as a tool for in vivo analysis of human muscles

An innovative approach based on hyperspectral imaging for an automatic characterization of post-earthquake building waste

Detecting Contaminants in Post-Consumer Plastic Packaging Waste by a Nir Hyperspectral Imaging-Based Cascade Detection Approach

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