Integration of big data for querying CAN bus data from connected car

Abstract

Data transmission by Connected Car via wireless communications technologies enable new in-car telematics services. The capability to efficiently process large volume of Controller Area Network (CAN) bus data within a reasonable time. Since these data are essential for many Connected Car applications, querying and extracting useful information using Hadoop framework will allow to enhance safety and driving experience. This paper studies design steps to take in consideration when implementing MapReduce patterns to analyses CAN bus data in order to produce useful data that are hosted in the cloud. In addition, we implement a mobile apps for collecting and transferring CAN bus data to remote data center which include application server and Hadoop ecosystem such Hive data warehouse. Experiment results show that MapReduce join algorithm is highly scalable and optimized for distributed computing than Statistical Analysis System (SAS) framework and HiveQL declarative language.