Abstract:Accurate predictions of vehicle mobility and density are necessary for a wide range of mobile applications, including VANETs, crowdsourcing, participatory sensing, network provisioning, and shared transportation. The difficulty of forecasting is exacerbated by the scarcity and scale of vehicular mobility data. Crowd management and navigation analysis of vehicular networks that make use of deep learning techniques are the focus of this study. Multihop path based edge computing is used to analyze vehicular netwo… Show more
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