TY - GEN
T1 - Environmental noise sensing approach based on volunteered geographic information and spatio-temporal analysis with machine learning
AU - Torres-Ruiz, Miguel
AU - Juárez-Hipólito, Juan H.
AU - Lytras, Miltiadis Demetrios
AU - Moreno-Ibarra, Marco
N1 - Publisher Copyright:
© Springer International Publishing Switzerland 2016.
PY - 2016
Y1 - 2016
N2 - In this paper a methodology for analyzing the behavior of the environmental noise pollution is proposed. It consists of a mobile application called ‘Noise Monitor’, which senses the environmental noise with the microphone sensor available in the mobile device. The georeferenced noise data constitute Volunteered Geographic Information that compose a large geospatial database of urban information of the Mexico City. In addition, a Web-GIS is proposed in order to make spatio-temporal analysis based on a prediction model, applying Machine Learning techniques to generate acoustic noise mapping with contextual information. According to the obtained results, a comparison between support vector machines and artificial neural networks were performed in order to evaluate the model and the behavior of the sensed data.
AB - In this paper a methodology for analyzing the behavior of the environmental noise pollution is proposed. It consists of a mobile application called ‘Noise Monitor’, which senses the environmental noise with the microphone sensor available in the mobile device. The georeferenced noise data constitute Volunteered Geographic Information that compose a large geospatial database of urban information of the Mexico City. In addition, a Web-GIS is proposed in order to make spatio-temporal analysis based on a prediction model, applying Machine Learning techniques to generate acoustic noise mapping with contextual information. According to the obtained results, a comparison between support vector machines and artificial neural networks were performed in order to evaluate the model and the behavior of the sensed data.
KW - Artificial neural network
KW - Mobile application
KW - Noise sensing
KW - Support vector machine
KW - Volunteered geographic information
UR - http://www.scopus.com/inward/record.url?scp=84978267458&partnerID=8YFLogxK
U2 - 10.1007/978-3-319-42089-9_7
DO - 10.1007/978-3-319-42089-9_7
M3 - Contribución a la conferencia
AN - SCOPUS:84978267458
SN - 9783319420882
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 95
EP - 110
BT - Computational Science and Its Applications - 16th International Conference, ICCSA 2016, Proceedings
A2 - Gervasi, Osvaldo
A2 - Apduhan, Bernady O.
A2 - Taniar, David
A2 - Torre, Carmelo M.
A2 - Wang, Shangguang
A2 - Misra, Sanjay
A2 - Murgante, Beniamino
A2 - Stankova, Elena
A2 - Rocha, Ana Maria A.C.
PB - Springer Verlag
T2 - 16th International Conference on Computational Science and Its Applications, ICCSA 2016
Y2 - 4 July 2016 through 7 July 2016
ER -
