{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,29]],"date-time":"2026-06-29T23:15:45Z","timestamp":1782774945956,"version":"3.54.5"},"reference-count":21,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2024,1,26]],"date-time":"2024-01-26T00:00:00Z","timestamp":1706227200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Ministero dell\u2019Universit\u00e0 e della Ricerca","award":["F83C21000170001"],"award-info":[{"award-number":["F83C21000170001"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Waste material classification is a challenging yet important task in waste management. The realization of low-cost waste classification systems and methods is critical to meet the ever-increasing demand for efficient waste management and recycling. In this paper, we demonstrate a simple, compact and low-cost classification system based on optical reflectance measurements in the short-wave infrared for the segregation of waste materials such as plastics, paper, glass, and aluminium. The system comprises a small set of LEDs and one single broadband photodetector. All devices are controlled through low-cost and low-power electronics, and data are gathered and managed via a computer interface. The proposed system reaches accuracy levels as high as 94.3% when considering seven distinct materials and 97.0% when excluding the most difficult to classify, thus representing a valuable proof-of-concept for future system developments.<\/jats:p>","DOI":"10.3390\/s24030809","type":"journal-article","created":{"date-parts":[[2024,1,30]],"date-time":"2024-01-30T12:06:58Z","timestamp":1706616418000},"page":"809","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":9,"title":["Waste Material Classification: A Short-Wave Infrared Discrete-Light-Source Approach Based on Light-Emitting Diodes"],"prefix":"10.3390","volume":"24","author":[{"given":"Anju","family":"Manakkakudy","sequence":"first","affiliation":[{"name":"Department of Industrial, Electronic and Mechanical Engineering, Roma Tre University, 00146 Rome, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5006-5505","authenticated-orcid":false,"given":"Andrea","family":"De Iacovo","sequence":"additional","affiliation":[{"name":"Department of Industrial, Electronic and Mechanical Engineering, Roma Tre University, 00146 Rome, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4312-6434","authenticated-orcid":false,"given":"Emanuele","family":"Maiorana","sequence":"additional","affiliation":[{"name":"Department of Industrial, Electronic and Mechanical Engineering, Roma Tre University, 00146 Rome, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Federica","family":"Mitri","sequence":"additional","affiliation":[{"name":"Department of Industrial, Electronic and Mechanical Engineering, Roma Tre University, 00146 Rome, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7111-3905","authenticated-orcid":false,"given":"Lorenzo","family":"Colace","sequence":"additional","affiliation":[{"name":"Department of Industrial, Electronic and Mechanical Engineering, Roma Tre University, 00146 Rome, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2024,1,26]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"43","DOI":"10.1002\/masy.201251005","article-title":"The Importance of Recycling in Solid Waste Management","volume":"320","author":"Kassim","year":"2012","journal-title":"Macromol. Symp."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"56","DOI":"10.1016\/j.wasman.2016.09.015","article-title":"A Review on Automated Sorting of Source-Separated Municipal Solid Waste for Recycling","volume":"60","author":"Gundupalli","year":"2017","journal-title":"Waste Manag."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"40","DOI":"10.1016\/j.wasman.2017.01.019","article-title":"Critical Review of Real-Time Methods for Solid Waste Characterisation: Informing Material Recovery and Fuel Production","volume":"61","author":"Vrancken","year":"2017","journal-title":"Waste Manag."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"259","DOI":"10.1016\/j.wasman.2022.05.015","article-title":"Optical Sensors and Machine Learning Algorithms in Sensor-Based Material Flow Characterization for Mechanical Recycling Processes: A Systematic Literature Review","volume":"149","author":"Kroell","year":"2022","journal-title":"Waste Manag."},{"key":"ref_5","doi-asserted-by":"crossref","unstructured":"Zhao, J., Tian, G., Qiu, Y., and Qu, H. (2021). Rapid Quantification of Active Pharmaceutical Ingredient for Sugar-Free Yangwei Granules in Commercial Production Using FT-NIR Spectroscopy Based on Machine Learning Techniques. Spectrochim. Acta Part A Mol. Biomol. Spectrosc., 245.","DOI":"10.1016\/j.saa.2020.118878"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"111339","DOI":"10.1016\/j.jfoodeng.2022.111339","article-title":"Near-Infrared Spectroscopy and Machine Learning for Classification of Food Powders during a Continuous Process","volume":"341","author":"Ozturk","year":"2023","journal-title":"J. Food Eng."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"778","DOI":"10.1109\/LGRS.2017.2681128","article-title":"Deep Learning Classification of Land Cover and Crop Types Using Remote Sensing Data","volume":"14","author":"Kussul","year":"2017","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_8","unstructured":"Vavilov, V.P., and Burleigh, D.D. (2008). Overview of SWIR Detectors, Cameras, and Applications, SPIE."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"313","DOI":"10.1007\/s00226-015-0785-x","article-title":"Application of Near-Infrared Spectroscopy for the Fast Detection and Sorting of Wood\u2013Plastic Composites and Waste Wood Treated with Wood Preservatives","volume":"50","author":"Mauruschat","year":"2016","journal-title":"Wood Sci. Technol."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"115","DOI":"10.1016\/j.saa.2018.03.006","article-title":"A Hierarchical Classification Approach for Recognition of Low-Density (LDPE) and High-Density Polyethylene (HDPE) in Mixed Plastic Waste Based on Short-Wave Infrared (SWIR) Hyperspectral Imaging","volume":"198","author":"Bonifazi","year":"2018","journal-title":"Spectrochim. Acta Part A Mol. Biomol. Spectrosc."},{"key":"ref_11","unstructured":"Valenta, C.R., and Kimata, M. (2019). SPIE Future Sensing Technologies, SPIE."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"95","DOI":"10.1016\/j.jfoodeng.2014.03.027","article-title":"LED-Induced Fluorescence System for Tea Classification and Quality Assessment","volume":"137","author":"Dong","year":"2014","journal-title":"J. Food Eng."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"322","DOI":"10.1108\/SR-12-2016-0276","article-title":"Portable Multispectral Imaging System Based on Raspberry Pi","volume":"37","author":"Carvajal","year":"2017","journal-title":"Sens. Rev."},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Sato, M., Yoshida, S., Olwal, A., Shi, B., Hiyama, A., Tanikawa, T., Hirose, M., and Raskar, R. (2015, January 18). SpecTrans: Versatile Material Classification for Interaction with Textureless, Specular and Transparent Surfaces. Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems, Seoul, Republic of Korea.","DOI":"10.1145\/2702123.2702169"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"9228","DOI":"10.1364\/AO.501582","article-title":"Material Classification Based on a SWIR Discrete Spectroscopy Approach","volume":"62","author":"Manakkakudy","year":"2023","journal-title":"Appl. Opt."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"38","DOI":"10.1016\/j.wasman.2017.07.023","article-title":"Development of a New Approach Based on Midwave Infrared Spectroscopy for Post-Consumer Black Plastic Waste Sorting in the Recycling Industry","volume":"68","author":"Rozenstein","year":"2017","journal-title":"Waste Manag."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"8144","DOI":"10.1016\/j.eswa.2010.12.156","article-title":"Hybrid Feature Selection by Combining Filters and Wrappers","volume":"38","author":"Hsu","year":"2011","journal-title":"Expert Syst. Appl."},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Gopika, N., and ME, A.M.K. (2018, January 15\u201316). Correlation Based Feature Selection Algorithm for Machine Learning. Proceedings of the 2018 3rd International Conference on Communication and Electronics Systems (ICCES), Coimbatore, India.","DOI":"10.1109\/CESYS.2018.8723980"},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"273","DOI":"10.1016\/S0004-3702(97)00043-X","article-title":"Wrappers for Feature Subset Selection","volume":"97","author":"Kohavi","year":"1997","journal-title":"Artif. Intell."},{"key":"ref_20","unstructured":"Soman, K.P., Loganathan, R., and Ajay, V. (2009). Machine Learning with SVM and Other Kernel Methods, PHI Learning Pvt. Ltd."},{"key":"ref_21","unstructured":"Singh, A., Thakur, N., and Sharma, A. (2016, January 16\u201318). A Review of Supervised Machine Learning Algorithms. Proceedings of the 2016 3rd International Conference on Computing for Sustainable Global Development (INDIACom), New Delhi, India."}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/24\/3\/809\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T13:49:45Z","timestamp":1760104185000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/24\/3\/809"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,1,26]]},"references-count":21,"journal-issue":{"issue":"3","published-online":{"date-parts":[[2024,2]]}},"alternative-id":["s24030809"],"URL":"https:\/\/doi.org\/10.3390\/s24030809","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,1,26]]}}}