Design of an automated system for the classification of plastic and glass bottles using sound
Nowadays, The Internet of Things (IoT) is a valuable tool which allows companies to automate and control their processes in a more efficient way by interconnecting hardware and software. For this project, we designed an automated system intended to classify elements in a recycling process. This was...
- Autores:
-
Restrepo Sánchez, Santiago
Sánchez Rodríguez, Juan Camilo
- Tipo de recurso:
- Trabajo de grado de pregrado
- Fecha de publicación:
- 2022
- Institución:
- Universidad de los Andes
- Repositorio:
- Séneca: repositorio Uniandes
- Idioma:
- eng
- OAI Identifier:
- oai:repositorio.uniandes.edu.co:1992/56422
- Acceso en línea:
- http://hdl.handle.net/1992/56422
- Palabra clave:
- IoT
MFFCs
Deep Learning
Mel Spectrogram
Audio
recycle
Internet de las cosas
Reciclaje
Aprendizaje automático (Inteligencia artificial)
Botellas
Ingeniería
- Rights
- openAccess
- License
- http://creativecommons.org/licenses/by-nc-nd/4.0/
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Design of an automated system for the classification of plastic and glass bottles using sound |
| title |
Design of an automated system for the classification of plastic and glass bottles using sound |
| spellingShingle |
Design of an automated system for the classification of plastic and glass bottles using sound IoT MFFCs Deep Learning Mel Spectrogram Audio recycle Internet de las cosas Reciclaje Aprendizaje automático (Inteligencia artificial) Botellas Ingeniería |
| title_short |
Design of an automated system for the classification of plastic and glass bottles using sound |
| title_full |
Design of an automated system for the classification of plastic and glass bottles using sound |
| title_fullStr |
Design of an automated system for the classification of plastic and glass bottles using sound |
| title_full_unstemmed |
Design of an automated system for the classification of plastic and glass bottles using sound |
| title_sort |
Design of an automated system for the classification of plastic and glass bottles using sound |
| dc.creator.fl_str_mv |
Restrepo Sánchez, Santiago Sánchez Rodríguez, Juan Camilo |
| dc.contributor.advisor.none.fl_str_mv |
Abolghasem Ghazvini, Sepideh Jiménez Vargas, José Fernando Lozano Garzon, Carlos Andres |
| dc.contributor.author.none.fl_str_mv |
Restrepo Sánchez, Santiago Sánchez Rodríguez, Juan Camilo |
| dc.contributor.jury.none.fl_str_mv |
Segura Quijano, Fredy Enrique Montes Arango, Ana María Otero Acosta, Julián David |
| dc.subject.keyword.none.fl_str_mv |
IoT MFFCs Deep Learning Mel Spectrogram Audio recycle |
| topic |
IoT MFFCs Deep Learning Mel Spectrogram Audio recycle Internet de las cosas Reciclaje Aprendizaje automático (Inteligencia artificial) Botellas Ingeniería |
| dc.subject.armarc.none.fl_str_mv |
Internet de las cosas Reciclaje Aprendizaje automático (Inteligencia artificial) Botellas |
| dc.subject.themes.es_CO.fl_str_mv |
Ingeniería |
| description |
Nowadays, The Internet of Things (IoT) is a valuable tool which allows companies to automate and control their processes in a more efficient way by interconnecting hardware and software. For this project, we designed an automated system intended to classify elements in a recycling process. This was done by applying Deep Learning and audio processing techniques, as well as by interconnecting a conveyor band, a robot arm, and an audio frequency sensor via various IoT communication protocols. The result is a fully automated system, which successfully classifies bottles based on the sound made when hit, with an accuracy of over 90% |
| publishDate |
2022 |
| dc.date.accessioned.none.fl_str_mv |
2022-03-18T15:38:52Z |
| dc.date.available.none.fl_str_mv |
2022-03-18T15:38:52Z |
| dc.date.issued.none.fl_str_mv |
2022-01-17 |
| dc.type.spa.fl_str_mv |
Trabajo de grado - Pregrado |
| dc.type.driver.spa.fl_str_mv |
info:eu-repo/semantics/bachelorThesis |
| dc.type.version.spa.fl_str_mv |
info:eu-repo/semantics/acceptedVersion |
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http://purl.org/coar/resource_type/c_7a1f |
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Text |
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http://purl.org/redcol/resource_type/TP |
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http://purl.org/coar/resource_type/c_7a1f |
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acceptedVersion |
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http://hdl.handle.net/1992/56422 |
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instname:Universidad de los Andes |
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reponame:Repositorio Institucional Séneca |
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repourl:https://repositorio.uniandes.edu.co/ |
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instname:Universidad de los Andes reponame:Repositorio Institucional Séneca repourl:https://repositorio.uniandes.edu.co/ |
| dc.language.iso.es_CO.fl_str_mv |
eng |
| language |
eng |
| dc.relation.references.es_CO.fl_str_mv |
"Simple audio recognition: Recognizing keywords TensorFlow Core", TensorFlow, 2021. [Online]. Available: https://www.tensorflow.org/tutorials/audio/simple-audio. L. Abaunza Barón, C. Castellanos Cuadrado and G. Malagón Rodriguez, "Perfilar 200 empresas transformadoras de plástico posconsumo en Bogotá.", 2019. "GitHub - timsainb/noisereduce: Noise reduction in python using spectral gating (speech, bioacoustics, audio, time-domain signals)", GitHub, 2021. [Online].Available: https://github.com/timsainb/noisereduce "librosa.feature.mfcc librosa 0.8.1 documentation", Librosa.org, 2021. [Online]. Available: https://librosa.org/doc/main/generated/librosa.feature.mfcc.html. "The URScript Programming Language", Universal Robots, 2018. [Online]. Available: https://s3-eu-west-1.amazonaws.com/ur-support-site/32554/scriptManual-3.5.4.pdf. FicsherTechnik Community Firmware Repository. Available: https://github.com/ftCommunity/ftcommunity-TXT/tree/v0.9.5 FischerTechnik Comunity Firmware Docs. Available: https://cfw.ftcommunity.de/ftcommunity-TXT/en/getting-started/ Buildroot Docs. Available: https://buildroot.org/docs.html |
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http://creativecommons.org/licenses/by-nc-nd/4.0/ |
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http://creativecommons.org/licenses/by-nc-nd/4.0/ http://purl.org/coar/access_right/c_abf2 |
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openAccess |
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7 paginas |
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application/pdf |
| dc.publisher.es_CO.fl_str_mv |
Universidad de los Andes |
| dc.publisher.program.es_CO.fl_str_mv |
Ingeniería de Sistemas y Computación Ingeniería Electrónica |
| dc.publisher.faculty.es_CO.fl_str_mv |
Facultad de Ingeniería |
| dc.publisher.department.es_CO.fl_str_mv |
Departamento de Ingeniería Sistemas y Computación Departamento de Ingeniería Eléctrica y Electrónica |
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Universidad de los Andes |
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Al consultar y hacer uso de este recurso, está aceptando las condiciones de uso establecidas por los autores.http://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/openAccesshttp://purl.org/coar/access_right/c_abf2Abolghasem Ghazvini, Sepideh1a73357e-0f9e-4267-ad22-ab14344c2607600Jiménez Vargas, José Fernandovirtual::15682-1Lozano Garzon, Carlos Andresvirtual::15683-1Restrepo Sánchez, Santiago99a1fa78-fdce-4a03-83c5-772f793dc898600Sánchez Rodríguez, Juan Camilo7f12f2ad-566d-4d83-9268-042f63c58107600Segura Quijano, Fredy EnriqueMontes Arango, Ana MaríaOtero Acosta, Julián David2022-03-18T15:38:52Z2022-03-18T15:38:52Z2022-01-17http://hdl.handle.net/1992/56422instname:Universidad de los Andesreponame:Repositorio Institucional Sénecarepourl:https://repositorio.uniandes.edu.co/Nowadays, The Internet of Things (IoT) is a valuable tool which allows companies to automate and control their processes in a more efficient way by interconnecting hardware and software. For this project, we designed an automated system intended to classify elements in a recycling process. This was done by applying Deep Learning and audio processing techniques, as well as by interconnecting a conveyor band, a robot arm, and an audio frequency sensor via various IoT communication protocols. The result is a fully automated system, which successfully classifies bottles based on the sound made when hit, with an accuracy of over 90%Ingeniero de Sistemas y ComputaciónIngeniero ElectrónicoPregrado7 paginasapplication/pdfengUniversidad de los AndesIngeniería de Sistemas y ComputaciónIngeniería ElectrónicaFacultad de IngenieríaDepartamento de Ingeniería Sistemas y ComputaciónDepartamento de Ingeniería Eléctrica y ElectrónicaDesign of an automated system for the classification of plastic and glass bottles using soundTrabajo de grado - Pregradoinfo:eu-repo/semantics/bachelorThesisinfo:eu-repo/semantics/acceptedVersionhttp://purl.org/coar/resource_type/c_7a1fTexthttp://purl.org/redcol/resource_type/TPIoTMFFCsDeep LearningMel SpectrogramAudiorecycleInternet de las cosasReciclajeAprendizaje automático (Inteligencia artificial)BotellasIngeniería"Simple audio recognition: Recognizing keywords TensorFlow Core", TensorFlow, 2021. [Online]. Available: https://www.tensorflow.org/tutorials/audio/simple-audio.L. Abaunza Barón, C. Castellanos Cuadrado and G. Malagón Rodriguez, "Perfilar 200 empresas transformadoras de plástico posconsumo en Bogotá.", 2019."GitHub - timsainb/noisereduce: Noise reduction in python using spectral gating (speech, bioacoustics, audio, time-domain signals)", GitHub, 2021. [Online].Available: https://github.com/timsainb/noisereduce"librosa.feature.mfcc librosa 0.8.1 documentation", Librosa.org, 2021. [Online]. Available: https://librosa.org/doc/main/generated/librosa.feature.mfcc.html."The URScript Programming Language", Universal Robots, 2018. [Online]. Available: https://s3-eu-west-1.amazonaws.com/ur-support-site/32554/scriptManual-3.5.4.pdf.FicsherTechnik Community Firmware Repository. Available: https://github.com/ftCommunity/ftcommunity-TXT/tree/v0.9.5FischerTechnik Comunity Firmware Docs. Available: https://cfw.ftcommunity.de/ftcommunity-TXT/en/getting-started/Buildroot Docs. 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