Automotive Application Using Edge Computing

Abstract

With a lot of new technologies requiring real-time data processing, cloud computing has become difficult to implement, due to the requirement of high bandwidth and high latency. To overcome this issue, edge computing is used to process data at the network's edge. Edge computing is a distributed computing paradigm which brings computation and data storage closer to the location where it is needed. It is used to process time-sensitive data. The model we implemented was using Linux Foundation's open-source platform EdgeX Foundry to create an edge computing device.

The model involved getting data from an on-board sensor (OBD-II) and GPS sensor of a car. The data is then observed and computed to the EdgeX server. The single server will send data to serve three real-life IoT use cases: auto insurance, supporting a smart city and building a personal driving record. The main aim of this model is to illustrate how Edge Computing can improve both latency and bandwidth usage needed for real-world IoT applications.