REAL-TIME VEHICLE TRACKING IN A BIG DATA ENVIRONMENT
Keywords:
Big data; big data analytics; participating vehicles (PV); non-participating vehicles (NPV); query vehicle data; Apache Kafka; Apache Storm; real-time tracking; stream processing.Abstract
With the development of the smart city and the Internet of Things, all vehicles are connected to each other, which improves the safety and efficiency of road transportation. In an Internet of Vehicles (IoV) environment, all vehicles transmit huge amounts of data in real time. I am very interested in the research fields of IoV and Big Data Analytics, which are still vibrant and rapidly developing. This paper presents a vehicle-tracking system for the Internet of Vehicles based on stream processing which allows for processing of huge amounts of IoV data streams for vehicle tracking in real-time. The system also deals with the tracking of vehicles which are not in the IoV system. Tracking is done in near real time, the aim being to reduce tracking latencies of vehicles. The proposed system is simulated and evaluated, and its performance is shown that the vehicles could be tracked even in a large scale of IoV deployment within milliseconds.
