An empirical study on real-time data analytics for connected cars: Sensor-based applications for smart cars

Jonghyuk Kim, Hyunwoo Hwangbo and Soyean Kim

International Journal of Distributed Sensor Networks, 2018, vol. 14, issue 1, 1550147718755290

Abstract: Connected cars, which are vehicles connected to wireless networks through the convergence of automotive and information technologies, have become an important topic of academic and industrial research on automobiles. In this research, we conducted a field experiment to understand vehicle maintenance mechanisms of a connected car platform. Specifically, we investigated the feasibility of prognostics and health management under different driving circumstances, with varying vehicle models, vehicle conditions, drivers’ propensity for speeding, and road conditions. We collected sensor data through a two-stage model of vehicle communication using an on-board diagnostics scanner and data transmission using wireless communication. We found that device defects can be predicted based on driving situations such as the driving mode, mechanical characteristics, and a driver’s speeding propensity.

Keywords: Connected car; prognostics and health management; big data analytics; sensor data (search for similar items in EconPapers)
Date: 2018
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:sae:intdis:v:14:y:2018:i:1:p:1550147718755290

DOI: 10.1177/1550147718755290

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