Internet of Vehicles (IoV) is an integral component of the Intelligent Transportation System (ITS) with the vision to acquire and process data for improving traffic safety. In IoV, vehicles communicate by exchanging messages with other vehicles and roadside infrastructure subsequently generating a large volume of data often referred to as big data, and which demands a massive storage and high computational capability with minimal possible delay. The aim of this paper is to take a step forward in outlining the current state-of-the-art in IoV and analyzing the improved data processing and storage features by utilizing big data analytics and fog computing paradigm. We further presented a preliminary simulation result to demonstrate that the introduction of fog improves the overall system performance by ensuring low-latency critical for especially vehicular safety applications. Moreover, this paper briefly discusses a fog computing based IoV crime assistant and highlight some of its challenges which needs to be addressed in order to enhance the performance of such systems.

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