title: An investigation of the usability of sound recognition for source separation of packaging wastes in reverse vending machines.
abstract: In this study, we investigate the usability of sound recognition for source separation of packaging wastes in reverse vending machines (RVMs). For this purpose, an experimental setup equipped with a sound recording mechanism was prepared. Packaging waste sounds generated by three physical impacts such as free falling, pneumatic hitting and hydraulic crushing were separately recorded using two different microphones. To classify the waste types and sizes based on sound features of the wastes, a support vector machine (SVM) and a hidden Markov model (HMM) based sound classification systems were developed. In the basic experimental setup in which only free falling impact type was considered, SVM and HMM systems provided 100% classification accuracy for both microphones. In the expanded experimental setup which includes all three impact types, material type classification accuracies were 96.5% for dynamic microphone and 97.7% for condenser microphone. When both the material type and the size of the wastes were classified, the accuracy was 88.6% for the microphones. The modeling studies indicated that hydraulic crushing impact type recordings were very noisy for an effective sound recognition application. In the detailed analysis of the recognition errors, it was observed that most of the errors occurred in the hitting impact type. According to the experimental results, it can be said that the proposed novel approach for the separation of packaging wastes could provide a high classification performance for RVMs.
authors.affiliation: Kocaeli University, Department of Environmental Engineering, 41380 Kocaeli, Turkey. Electronic address: kemal.korucu@gmail.com.
authors.forename: M Kemal
authors.initials: MK
authors.lastname: Korucu
authors.affiliation: Kocaeli University, Department of Mechanical Engineering, 41380 Kocaeli, Turkey.
authors.forename: Özgür
authors.initials: Ö
authors.lastname: Kaplan
authors.affiliation: Kocaeli University, Department of Electronics and Communications Engineering, 41380 Kocaeli, Turkey.
authors.forename: Osman
authors.initials: O
authors.lastname: Büyük
authors.affiliation: Kocaeli University, Department of Electronics and Communications Engineering, 41380 Kocaeli, Turkey.
authors.forename: M Kemal
authors.initials: MK
authors.lastname: Güllü
mesh_terms: D008390:Markov Chains; D008962:Models, Theoretical; D019064:Product Packaging; D062611:Solid Waste / Q000032:analysis*; D013016:Sound; D060388:Support Vector Machine
chemical_list: D062611:Solid Waste
keywords: Hidden Markov model; Municipal solid wastes; Reverse vending machines; Sound of packaging wastes; Support vector machines; Voice recognition