Sensor signal preprocessing techniques for analysis and prediction
- Autores
- Monte, Gustavo Eduardo
- Año de publicación
- 2008
- Idioma
- español castellano
- Tipo de recurso
- artículo
- Estado
- versión aceptada
- Descripción
- This paper presents a signal processing technique that employs oversampling and identification of important samples to determine signal behavior and tendency. Sensor signal windows of random lengths are vectorized and classified to fit into only eight predefined types, and in conjunction with time indexes vectors, they can predict future values, steady state value and an estimation of the sensor signal function. The techniques developed allow the representation of any class of sensor signal for further analysis. The computational cost is quite low so they can be implemented in real time into smart sensors with low cost microcontrollers. Therefore, it is also an ideal technique to preprocess the sensor signal to mark regions of interest to more sophisticated processes.
Fil: Monte Gustavo, Eduardo. Universidad Tecnológica Nacional. Facultad regional del Neuquen; Argentina.
Peer Reviewed - Materia
- Sensor signal preprocessing techniques for analysis and prediction
- Nivel de accesibilidad
- acceso abierto
- Condiciones de uso
- 2023-12-06T21:01:06Z
- Repositorio
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- Institución
- Universidad Tecnológica Nacional
- OAI Identificador
- oai:ria.utn.edu.ar:20.500.12272/9128
Ver los metadatos del registro completo
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Sensor signal preprocessing techniques for analysis and predictionMonte, Gustavo EduardoSensor signal preprocessing techniques for analysis and predictionThis paper presents a signal processing technique that employs oversampling and identification of important samples to determine signal behavior and tendency. Sensor signal windows of random lengths are vectorized and classified to fit into only eight predefined types, and in conjunction with time indexes vectors, they can predict future values, steady state value and an estimation of the sensor signal function. The techniques developed allow the representation of any class of sensor signal for further analysis. The computational cost is quite low so they can be implemented in real time into smart sensors with low cost microcontrollers. Therefore, it is also an ideal technique to preprocess the sensor signal to mark regions of interest to more sophisticated processes.Fil: Monte Gustavo, Eduardo. Universidad Tecnológica Nacional. Facultad regional del Neuquen; Argentina.Peer Reviewed2023-12-06T21:01:06Z2023-12-06T21:01:06Z2008-11-13info:eu-repo/semantics/articleinfo:eu-repo/semantics/acceptedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articulopdfapplication/pdf978-1-4244-1767-4http://hdl.handle.net/20.500.12272/9128spainfo:eu-repo/semantics/openAccess2023-12-06T21:01:06Zhttp://creativecommons.org/licenses/by-nc-nd/4.0/Attribution-NonCommercial-NoDerivatives 4.0 InternacionalCreative Commosreponame:Repositorio Institucional Abierto (UTN)instname:Universidad Tecnológica Nacional2026-09-24T12:46:39Zoai:ria.utn.edu.ar:20.500.12272/9128instacron:UTNInstitucionalhttp://ria.utn.edu.ar/Universidad públicaNo correspondehttp://ria.utn.edu.ar/oaigestionria@rec.utn.edu.ar; fsuarez@rec.utn.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:a2026-09-24 12:46:40.679Repositorio Institucional Abierto (UTN) - Universidad Tecnológica Nacionalfalse |
| dc.title.none.fl_str_mv |
Sensor signal preprocessing techniques for analysis and prediction |
| title |
Sensor signal preprocessing techniques for analysis and prediction |
| spellingShingle |
Sensor signal preprocessing techniques for analysis and prediction Monte, Gustavo Eduardo Sensor signal preprocessing techniques for analysis and prediction |
| title_short |
Sensor signal preprocessing techniques for analysis and prediction |
| title_full |
Sensor signal preprocessing techniques for analysis and prediction |
| title_fullStr |
Sensor signal preprocessing techniques for analysis and prediction |
| title_full_unstemmed |
Sensor signal preprocessing techniques for analysis and prediction |
| title_sort |
Sensor signal preprocessing techniques for analysis and prediction |
| dc.creator.none.fl_str_mv |
Monte, Gustavo Eduardo |
| author |
Monte, Gustavo Eduardo |
| author_facet |
Monte, Gustavo Eduardo |
| author_role |
author |
| dc.subject.none.fl_str_mv |
Sensor signal preprocessing techniques for analysis and prediction |
| topic |
Sensor signal preprocessing techniques for analysis and prediction |
| dc.description.none.fl_txt_mv |
This paper presents a signal processing technique that employs oversampling and identification of important samples to determine signal behavior and tendency. Sensor signal windows of random lengths are vectorized and classified to fit into only eight predefined types, and in conjunction with time indexes vectors, they can predict future values, steady state value and an estimation of the sensor signal function. The techniques developed allow the representation of any class of sensor signal for further analysis. The computational cost is quite low so they can be implemented in real time into smart sensors with low cost microcontrollers. Therefore, it is also an ideal technique to preprocess the sensor signal to mark regions of interest to more sophisticated processes. Fil: Monte Gustavo, Eduardo. Universidad Tecnológica Nacional. Facultad regional del Neuquen; Argentina. Peer Reviewed |
| description |
This paper presents a signal processing technique that employs oversampling and identification of important samples to determine signal behavior and tendency. Sensor signal windows of random lengths are vectorized and classified to fit into only eight predefined types, and in conjunction with time indexes vectors, they can predict future values, steady state value and an estimation of the sensor signal function. The techniques developed allow the representation of any class of sensor signal for further analysis. The computational cost is quite low so they can be implemented in real time into smart sensors with low cost microcontrollers. Therefore, it is also an ideal technique to preprocess the sensor signal to mark regions of interest to more sophisticated processes. |
| publishDate |
2008 |
| dc.date.none.fl_str_mv |
2008-11-13 2023-12-06T21:01:06Z 2023-12-06T21:01:06Z |
| dc.type.none.fl_str_mv |
info:eu-repo/semantics/article info:eu-repo/semantics/acceptedVersion http://purl.org/coar/resource_type/c_6501 info:ar-repo/semantics/articulo |
| format |
article |
| status_str |
acceptedVersion |
| dc.identifier.none.fl_str_mv |
978-1-4244-1767-4 http://hdl.handle.net/20.500.12272/9128 |
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978-1-4244-1767-4 |
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http://hdl.handle.net/20.500.12272/9128 |
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spa |
| language |
spa |
| dc.rights.none.fl_str_mv |
info:eu-repo/semantics/openAccess 2023-12-06T21:01:06Z http://creativecommons.org/licenses/by-nc-nd/4.0/ Attribution-NonCommercial-NoDerivatives 4.0 Internacional Creative Commos |
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openAccess |
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2023-12-06T21:01:06Z http://creativecommons.org/licenses/by-nc-nd/4.0/ Attribution-NonCommercial-NoDerivatives 4.0 Internacional Creative Commos |
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pdf application/pdf |
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