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

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.

Enhancing ERP Responsiveness Through Big Data Technologies: An Empirical Investigation

“…The survey carried out by the ERP buyer’s profile for growing companies predicts that by the next 3–5 years; at least 53% of the companies worldwide will move to cloud ERPs completely (Mintchell, 2018 ). ERP systems seamlessly integrate different business processes across the departments and functional areas into a centralized system (Davenport, 1998 ; Hashem et al, 2015 ; Jayawickrama et al, 2017 ; Kim et al, 2018 ; Mahmood & Lloyd, 2017 ; Saxena, 2016 ; Shi & Wang, 2018 ; Wagner et al, 2004 ). Those systems connect people, processes, data and things in an intelligent and strategic manner that allows organizations to create value from data streams generated through ERP systems (Grover et al, 2018 ; Lehrer et al, 2018 ).…”

“…Big data generated through various mediums (e.g., social media, web searches, smart watches and customer tracking using business intelligence) can be used for predictions, so that business processes can be optimized (Bekker, 2018 ; Kim et al, 2018 ; Marr, 2019 ; Rastogi, 2018 ; Wickman et al, 2018 ). For example, the big data generated through social media interactions can be used to predict future buying intensions of the individuals.…”

The Role of IoT Devices in Sustainable Car Expenses in the Context of the Intelligent Mobility: A Comparative Approach

“…Regarding what can be considered car expenses and how they vary, Kim, Hwangbo, and Kim [21] indicate that expenditures may vary depending on the type of driving, the driving circumstances, the type of car, the speed at which it is driven, and other factors related to car use. There are other studies [22] that show that 44.33% of buyers of electric or hybrid vehicles are also buyers of home solar panels.…”

Empowering Commercial Vehicles through Data-Driven Methodologies

“…The parameters collected telematically on the vehicle can be exploited on the business side mainly for two functions: (i) predictive maintenance and (ii) remaining useful life (RUL) estimation. Regarding the first research challenge, work on this issue has, for example, been presented in [8], which attempts to estimate the probability of fuel pump failure, or in [9], where authors investigated the feasibility of prognostics and health management under different driving circumstances. Instead, the RUL estimation consists of estimating the residual life of a given vehicle (in terms of the number of kilometers it can still cover or days of activity).…”

“…• First of all, unlike [7,9], we do not consider a generic connected vehicle case (cars), but we focus on the telematics of trucks. Not much work in this context has been performed on heavy trucks at present, leaving plenty of room for new analyses and experiments.…”