An Application Programming Interface for Advanced Analytics of Contextually Enriched Automotive Data

Abstract

The amount of data generated by vehicles has increased in recent years. Automotive manufacturers employ data processing and analysis to gain insights from the data they collect from vehicles. Contextually enriching vehicle-generated data with information describing location, weather and traffic is a way to generate even more insights into driver behaviour profiling and transportation sustainability. As the contextually enriched automotive data is usually stored in big data storage platforms, a middleware solution is needed to provide an abstraction layer for the stored data. Application programming interfaces (APIs) are commonly used as a bridge between the data consumers and the collected data. This paper describes one such API for advanced analytics of contextually enriched automotive data. The collection, contextual enrichment and data model of the data offered by the API is shown, along with the APIs architecture and available functionalities. To show the usability of the API, two use cases from the automotive domain are demonstrated: (i) contextually enriched automotive data visualization; and (ii) eco-efficient driving pattern evaluation.