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Current urbanization trends are leading to heightened demand of smarter technologies to facilitate a variety of applications in smart cities and, particularly, Intelligent Transportation Systems (ITS). Automated crowdsensing constitutes a strong base for ITS applications by providing novel and rich data streams regarding congestion tracking, public transportation monitoring, and real-time navigation. This high amount of data can be collected from diverse heterogenous sources such as infrastructure-based sensors, vehicle social network, human input, official agents, and social media. This abundant and diverse data can be exploited to help drivers, passengers, and ITS users in general assess the situation of ITS systems, evaluate traffic network statuses, improve the navigation of vehicles in urban areas, and enhance the quality of services of several transportation means.