Abstract
Understanding human mobility in dynamic environments, such as our cities, is a crucial step toward the development of our economy, our environment, our transportation, as well as our well-being. Therefore, there is a need to rely on a sensor or a source of information, such as mobile phone data, that can help us to sense these urban dynamics. From this viewpoint, we are focusing on demonstrating and presenting our concept idea that relies on a new method based on switching Kalman filter that enables the extraction of mobility patterns and through its analysis discovering mobility hubs where the urban mobility converges or diverges using mobile data, especially CDR data.
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