Mobility Data Fusion and Management is a multidisciplinary approach that involves the collection, integration, processing, and analysis of diverse data sources related to mobility, such as location data from connected vehicles, GPS-enabled devices, and other sensors. It aims to efficiently manage and make sense of large volumes of mobility data to derive valuable insights, support decision-making, and improve transportation and urban planning. In particular, EMERALDS project will investigate trajectory simplification/smoothing methods to reduce the data size, lossless data compression, depending on the sampling rate and the change in temporal properties.
