OBD-II and Big Data: A Powerful Combination to Solve the Issues of Automobile Care

Abstract

Automobile care is the next big thing that needs to be monitored to control the air and sound pollution levels on this planet. In an attempt to achieve this, we propose continuous monitoring of various parameters in the automobile as part of our project. Through this paper we wish to compile the excellent work accomplished by various authors in the field of Big data, OBD-II, CAN bus, and OBD-III. Big Data is an expression used for a huge amount of structured and unstructured data which is too large to be processed using conventional software and database methodologies and techniques. In this paper, we shall detail various language/tools needed for big data analysis like Hadoop, Python, Spark, R, and Matlab. OBD (On Board Diagnostics) is a self-diagnostics system constructed inside the car or vehicle and commissioned at the time of manufacturing. OBD-II is a tool that has a defined function and responsibility to make a diagnosis and report the state and situation of car’s engine and health. CAN (Controller Area Network) bus is a system prepared for intercommunication of car or vehicle devices. This bus permits communication of plenty of microcontrollers and various types of devices with each other in real-time and moreover without a host computer. Addressing schemes are not needed by CAN bus, because the network nodes use unique identifiers. OBD-III can be termed as a program that can reduce the waiting time between recognition of an OBD-II system’s emissions malfunction and repair of the vehicle. OBD-III will be forecasted as the future of automobile diagnostic systems. An endeavor has been made to cover the interesting portions and matter on Big data, CAN bus, and OBD-II.