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This paper presents an approach for an automatic surveillance system in public transport by analyzing audio signals recorded in the vehicle in order to detect several abnormal behaviors. We try to visualize audio signals by projection methods like PCA and kernel PCA. We use also unsupervised classification (clustering) methods to separate the audio signals into their components precisely we are using Kmeans and kernel K-means.