Definition
Big Data in the automotive industry is an effort to highlight the significance and relation of Big Data Analytics in the emerging automotive industry. Automotive industry is no more a property of conventional original equipment manufacturers (OEMs), but IT companies are pouring into the industry and giving tough challenge to big brands. Big Data has played a significant role in a wide range of areas, for example, training algorithms for autonomous driving, data clustering, consumer studies, understanding the relationship between customer demand and technology impact, evaluation for better future strategies for R&D and sales, etc.
Overview
The arrival of the fourth industrial revolution has brought significant challenges for the industry (Bloem et al. 2014). Numerous industries which thrived in the past now face mere extinction. One such example is the emergence of touch screens in the mobile phones. This innovation literally wiped out numerous cellular OEMs when they failed...
References
Al Najada H, Mahgoub I (2016) Autonomous vehicles safe-optimal trajectory selection based on big data analysis and predefined user preferences. In: Ubiquitous computing, electronics & mobile communication conference (UEMCON), IEEE annual. IEEE, pp 1–6. http://ieeexplore.ieee.org/abstract/document/7777922/
Amini S, Gerostathopoulos I, Prehofer C (2017) Big data analytics architecture for real-time traffic control. In: 2017 5th IEEE international conference on models and technologies for intelligent transportation systems (MT-ITS). IEEE, pp 710–715. http://ieeexplore.ieee.org/abstract/document/7777922/
Bloem J, Doorn MV, Duivestein S, Excoffier D, Maas R, Ommeren EV (2014) The fourth industrial revolution – things to tighten the link between IT and OT. Sogeti VINT2014
Daniel A, Subburathinam K, Paul A, Rajkumar N, Rho S (2017) Big autonomous vehicular data classifications: towards procuring intelligence in ITS. Veh Commun 9:306–312. ISSN: 2214-2096
Deloitte (2014) Driving through the consumer’s mind: steps in the buying process. https://www2.deloitte.com/content/dam/Deloitte/in/Documents/manufacturing/in-mfg-dtcm-steps-in-the-buying-process-noexp.pdf.~Accessed 12 Dec 2017
IBM Institute of Business Value (2014) Automotive 2025: industry without borders. https://www-935.ibm.com/services/multimedia/GBE03640USEN.pdf. Accessed 29 Dec 2017
Liu J, Wan J, Zeng B, Wang Q, Song H, Qiu M (2017) A scalable and quick-response software defined vehicular network assisted by mobile edge computing. IEEE Commun Mag 55(7):94–100
McKinsey & Company (2016) Monetizing car data. https://webcache.googleusercontent.com/search?q=cache:dzKdWumkARcJ:https://www.mckinsey.com/~/media/McKinsey/Industries/Automotive%2520and%2520Assembly/Our%2520Insights/Monetizing%2520car%2520data/Monetizing-car-data.ashx+&cd=1&hl=en&ct=clnk&gl=de. Accessed 12 Dec 2017
Nokia (2017) Nokia connected vehicles V2X. https://onestore.nokia.com/asset/200766/Nokia_Connected_Vehicles_V2X_Flyer_Document_EN.pdf. Accessed 18 Dec 2017
Pickhard F (2016) Measuring “everything” big data in automotive engineering. ATZelektronik Worldwide 11(1):64
SAS (2015) The connected vehicle: big data, big opportunities. https://www.sas.com/content/dam/SAS/en_us/doc/whitepaper1/connected-vehicle-107832.pdf. Accessed 25 Dec 2017
Sherif AB, Rabieh K, Mahmoud MM, Liang X (2017) Privacy-preserving ride sharing scheme for autonomous vehicles in big data era. IEEE IoT J 4(2):611–618
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Section Editor information
Rights and permissions
Copyright information
© 2018 Springer International Publishing AG, part of Springer Nature
About this entry
Cite this entry
Mughal, A.A. (2018). Big Data in Automotive Industry. In: Sakr, S., Zomaya, A. (eds) Encyclopedia of Big Data Technologies. Springer, Cham. https://doi.org/10.1007/978-3-319-63962-8_34-1
Download citation
DOI: https://doi.org/10.1007/978-3-319-63962-8_34-1
Received:
Accepted:
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-63962-8
Online ISBN: 978-3-319-63962-8
eBook Packages: Springer Reference MathematicsReference Module Computer Science and Engineering