Internet of vehicles in big data era
By Wenchao Xu, Haibo Zhou, Nan Cheng, Feng Lyu, Weisen Shi, Jiayin Chen, Xuemin Shen. IEEE/CAA Journal of Automatica Sinica, 2018
469 citations recorded by the source corpus.
Subfields: Automotive Engineering, Computer Vision and Pattern Recognition, Electrical and Electronic Engineering
View Paper: https://www.semanticscholar.org/paper/3527f43e8156d1bf5a0998405047c98036d172f0
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Automotive Engineering
In Computer Vision and Pattern Recognition
- Xiansheng Hua
- Khaled Ben Letaief
- Shengli Xie
- Jiawen Kang
- Chunyan Miao
- Dusist Niyato
- Wei Yang Bryan Lim
- Cyril Leung
In Electrical and Electronic Engineering
- Yan Zhang
- Dusist Niyato
- Sabita Maharjan
- Zehui Xiong
- Khaled Ben Letaief
- Jiawen Kang
- Jun Zhang
- Rong Yu
Citations in the corpus
- Towards Federated Learning in UAV-Enabled Internet of Vehicles: A Multi-Dimensional Contract-Matching Approach (2020, background): “…in the Internet of Things (IoT) and edge computing paradigm, traditional Vehicular Ad-Hoc Networks (VANETs) that focus mainly on Vehicle-to-Vehicle (V2V) and Vehicle-to-Infrastructure (V2I) communications [1], [2] are gradually evolving into the Internet of Vehicles (IoV) paradigm [3], [4].”
- Mobile Edge Intelligence and Computing for the Internet of Vehicles (2019, background): “To extend the capabilities of VANET, the Internet of Vehicles (IoV) has been proposed to form a global network of vehicles, evoking collaborations between heterogeneous communication systems to provide reliable Internet services [9], [10].”
- Evolutionary V2X Technologies Toward the Internet of Vehicles: Challenges and Opportunities (2020, background): “, ITS, advanced driving, and autonomous vehicles, conventional connected vehicles are evolving from V2X communications to the IoV [1].”
- Blockchain for Secure and Efficient Data Sharing in Vehicular Edge Computing and Networks (2019, background): “For example, a self-driving vehicle can create 1 GB data per second from cameras, radar, GPS, etc. [1].”