Chapter 15 - Vehicle telematics: An Internet of Things and Big Data approach

Abstract

Telematics refers to the transmission of information to and from assets using telecommunication networks. The field of telematics originated with the introduction of the Global Positioning System (GPS), used by the US military. It was opened to public usage in 1985 and saw simple applications such as panic buttons, installed in vehicles for reporting emergencies. Telematics has evolved beyond these initial applications. Today, telematics has the potential to revolutionize the automotive industry with applications that were not possible till now. Telematics has always involved transferring information from assets to a computational unit that extracts insights from the information and either makes it available to the end user or uses it to control other assets. Earlier wires were used for this exchange, but with the advent of modern telecommunication techniques such as Bluetooth and cellular networks, the exchange can be directly from the device without relying on physical wires. Telematics has moved today to open platforms such as Google Cloud and Amazon AWS to allow integration with other software and accessories. Similarly, large volumes of collected structured, unstructured, or semistructured data that cannot be meaningfully processed using standard data management techniques is called Big Data. In order to insightfully obtain needed information from the Big Data, appropriate tools are necessary to perform data collection, storage, and processing routines. with cloud computing, distributed storage, and advanced data mining techniques, Big Data allows the efficient processing of huge amounts of data to extract value and gain insights. Data mining techniques used for extraction under Big Data are very different from conventional statistical data analysis. The Big Data technology has opened the doors to a range of innovative opportunities in vehicle telematics. It builds meaningful insights for both automobile companies and customers to better control and maintain their vehicles. Therefore, this chapter presents some use cases of Big Data in vehicle telematics such as predicting vehicle reaction time, predicting per kilometer costs of trips, predicting CO2 emission, predicting vehicle health diagnosis, and classifying driver behaviors.