Abstract
Smart cars, with the emergence of the Internet of Vehicles (IoV), are expected to generate huge volumes of data at rates that typical data management systems will not be able to handle. Such data can be extremely useful to both analytics and machine learning applications. This paper discusses and demonstrates the process of architecting and building a scalable data management system for the IoV in a smart city environment, using Apache Spark, Apache Kafka and Apache Cassandra, which results in a scalable, resilient and fault-tolerant data management system that facilitates performing big data analytics and scalable machine learning on IoV data.
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