Intelligent Applications to Smart Cars Based on 5G MEC with Iot

DOI

10.2991/assehr.k.220701.046How to use a DOI?

Keywords

Mobile Edge Computing; Digital Twin; Autonomous driving; Internet of Things (IoT); V2X Communication

Abstract

With the rise of 5G as a burgeoning computing method, MEC technology has gained traction. It gives a revolution in automotive field with its low latency and high response. The article introduces the concept of MEC and gives coordinate development status first. Compared to traditional network and cloud computing, the MEC can offer low latency and high computing power service. Then, three core technologies are discussed and analyzed in depth: sensor, digital twin, and V2X communication. The sensor contains three typical methods of object detection and the MEC will support the CNN algorithm to give precise results in hardware. The digital twin can also apply with MEC as effective tools in the manufacturing of the smart car. With MEC assistance, the V2X can reduce the delay and packet loss. Further examples of applications based on MEC are given. After that, the advantages and limitations of mentioned applications are analyzed. Finally, the conclusion gives a brief overview of the automotive industry that the MEC can decrease the latency and offering extraordinary computing power to integrate different parts. It also advises the practitioners to give further experiments in three key parts of smart car for their potential value and well feasibility. The further trend of MEC in the smart vehicle and the defects that need further work are reviewed.

Copyright

© 2022 The Authors. Published by Atlantis Press SARL.

Open Access

This is an open access article distributed under the CC BY-NC 4.0 license.

Download article (PDF)

TY  - CONF
AU  - Zhenyi Zhu
PY  - 2022
DA  - 2022/07/04
TI  - Intelligent Applications to Smart Cars Based on 5G MEC with Iot
BT  - Proceedings of the 2022 International Conference on Science and Technology Ethics and Human Future (STEHF 2022)
PB  - Atlantis Press
SP  - 228
EP  - 231
SN  - 2352-5398
UR  - https://doi.org/10.2991/assehr.k.220701.046
DO  - 10.2991/assehr.k.220701.046
ID  - Zhu2022
ER  -