Vehicle recognition by using acoustic signature and classic DSP techniques
HTML

Palabras clave

Acoustic signature
correlation
vehicle traffic

Cómo citar

Díaz Velásquez, M. F., & Guerrero Ramírez, J. E. (2016). Vehicle recognition by using acoustic signature and classic DSP techniques. Revista De Investigación Agraria Y Ambiental, 7(1). https://doi.org/10.22490/21456453.1621

Resumen

This paper shows the application of the classic technique of digital signal processing (DSP), the cross-correlation, used for the detection of acoustic signatures of road traffic in Cali city, Colombia. Future goal is to build a detection software that through real time measures allows us estimate the levels of acoustic pollution in the city by using simulation models of road traffic, in the framework of environmentally-friendly smart cities. Final results of the experimental tests showed an accuracy of 71.43% for specific vehicle detection.

https://doi.org/10.22490/21456453.1621
HTML

Citas

Alcaldía de Santiago de Cali. (2016). Cali en Cifras, Capítulo Generalidades, Información Geográfica. Retrieved from http://www.cali.gov.co/publicaciones/ cali_en_cifras_planeacion_pub

Alesis.com. (2011). Alesis twotrack brochure [Computer software manual]. Retrieved from http:// www.fullcompass.com/common/files/16187-AlesisTwoTrackBrochure.pdf

Europeo, P. (2014). Mapping Smart Cities in the EU (Tech. Rep.). Retrieved from http://www.europarl.europa.eu/RegData/etudes/etudes/join/2014/507480/IPOL-ITRE_ET(2014)507480_EN.pdf

García, B., Francisco, S., & Garrido, J. (2003). La contaminación acústica en nuestras ciudades ( La contaminación acústica en nuestras ciudades). Fundación la Caixa. Retrieved from https://obrasocial.lacaixa.es/ deployed_files/obrasocial/Estaticos/pdf/Estudios_sociales/es12_esp.pdf

Garcia, N. E. (2015). Actualización del mapa de ruido ambiental periodos de tiempo diurno y nocturno entre semana y fin de semana (Tech. Rep.). Santiago de Cali: Pontificia Universidad Javeriana. Retrieved from http:// www.cali.gov.co/salud/publicaciones/mapa_de_ruido_santiago_de_cali_pub

Kandpal, M., Kakar, V. K., & Verma, G. (2013, dec). Classification of ground vehicles using acoustic signal processing and neural network classifier. In Signal processing and communication (icsc), 2013 international conference on (pp. 512–518). doi: 10.1109/ICSPCom.2013.6719846

Lu, B., Dibazar, A., & Berger, T. W. (2008, jun). Non-linear Hebbian Learning for noise-independent vehicle sound recognition. In 2008 ieee international joint conference on neural networks (ieee world congress on computational intelligence) (pp. 1336–1343). doi: 10.1109/IJCNN.2008.4633971

Munich, M. E. (2004, sep). Bayesian subspace methods for acoustic signature recognition of vehicles. In Signal processing conference, 2004 12th european (pp. 2107–2110).

Proakis, J. G., & Manolakis, D. G. (1996). Digital Signal Processing (3rd Ed.): Principles, Algorithms, and Applications. Upper Saddle River, NJ, USA: Prentice-Hall, Inc.

Rahim, N. A., Paulraj, M. P., Adom, A. H., & Sundararaj, S. (2010, may). Moving vehicle noise classification using backpropagation algorithm. In Signal processing and its applications (cspa), 2010 6th international colloquium on (pp. 1–6). doi: 10.1109/CSPA.2010.5545231

Recuero Lopez, M. (1999). Ingeniería acústica. Paraninfo. Retrieved from https://books.google.es/books?id=NsvoAAAACAAJ

Segués, F. (2005). Estrategia de elaboración de un mapa de ruido (Tech. Rep.). Centro de Estudios y Experimentación de Obras Públicas (CEDEX).

Tobías, A., Díaz, J., Recio, A. & Linares, C. (2014). Noise levels and cardiovascular mortality: a case-crossover analysis. European Journal of Preventive Cardiology. doi: 10.1177/2047487314528108

Creative Commons License
Esta obra está bajo licencia internacional Creative Commons Reconocimiento-NoComercial-CompartirIgual 4.0.

Derechos de autor 2017 Revista de Investigación Agraria y Ambiental

Detalle de visitas

HTML: 356
Resumen: 294

Descargas

La descarga de datos todavía no está disponible.