Abstract
Big Data for IoV development is about turning imperfect, complex, often unstructured data into actionable information, which implies leveraging advanced computational tools to visualize trends and correlations within and across large IoV data sets that would otherwise remain undiscovered. The current research on IoV and cloud system is focusing on data in terms of its complexity and the connections to share it, in consideration of costs and efficiency. However, in few years after, there will be IoV populated and heterogeneous networked embedded devices, which are generating large-scale data in an explosion fashion. The intelligent IoV system should be also capable of learn, think and understand the physical systems by themselves. Therefore, in this paper, we investigate and introduced a paradigm augmenting big data for IoV intelligent system to optimize massive data exploration in the field. The paradigm of big data augmentation is a systematic approach to development raises great expectations and concern to the analytical value of large-scale data that address IoV in the natural progression of intelligent IoV and cloud computing. The intelligent IoV technology is transforming to cloud system to satisfy a variety of IoV applications and user needs, which provide analytic and access of massive data.
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Gebremeskel, G.B., Chai, Y., Yang, Z. (2014). The Paradigm of Big Data for Augmenting Internet of Vehicle into the Intelligent Cloud Computing Systems. In: Hsu, R.CH., Wang, S. (eds) Internet of Vehicles – Technologies and Services. IOV 2014. Lecture Notes in Computer Science, vol 8662. Springer, Cham. https://doi.org/10.1007/978-3-319-11167-4_25
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DOI: https://doi.org/10.1007/978-3-319-11167-4_25
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