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The method combines spatial impulse response analysis with machine learning (ML) techniques, offering a unique and effective approach for sound-based classification that can be extended to various domains beyond waste management. By employing a buzzer-generated sine sweep signal, we create a distinctive signature specific to the fill level of the waste container. This signature, once accurately decoded, is then interpreted by a specially developed ensemble learning algorithm. Our approach achieves a classification accuracy of over 90% when implemented locally on a development board, optimizing operational efficiencies and eliminating the need to delegate complex classification tasks to external entities. Using low-cost and energy-efficient hardware components, our method offers a cost-effective approach that contributes to sustainable and efficient waste management practices, providing a reliable and locally deployable solution.<\/jats:p>","DOI":"10.1007\/s44163-024-00165-w","type":"journal-article","created":{"date-parts":[[2024,9,26]],"date-time":"2024-09-26T18:02:09Z","timestamp":1727373729000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Spatial impulse response analysis and ensemble learning for efficient precision level sensing"],"prefix":"10.1007","volume":"4","author":[{"ORCID":"https:\/\/orcid.org\/0009-0003-6531-8626","authenticated-orcid":false,"given":"Berkay","family":"Cetkin","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9869-0219","authenticated-orcid":false,"given":"Lejla","family":"Begic Fazlic","sequence":"additional","affiliation":[]},{"given":"Kristof","family":"Ueding","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0194-6194","authenticated-orcid":false,"given":"R\u00fcdiger","family":"Machhamer","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7532-4523","authenticated-orcid":false,"given":"Achim","family":"Guldner","sequence":"additional","affiliation":[]},{"given":"Lars","family":"Creutz","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0009-0000-6542-2229","authenticated-orcid":false,"given":"Stefan","family":"Naumann","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6786-6664","authenticated-orcid":false,"given":"Guido","family":"Dartmann","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2024,9,26]]},"reference":[{"key":"165_CR1","doi-asserted-by":"publisher","DOI":"10.1007\/s10311-023-01604-3","author":"B Fang","year":"2023","unstructured":"Fang B, Yu J, Chen Z, Osman A, Farghali M, Ihara I, Hamza E, Rooney D, Yap P-S. 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