Summary of The Roles Of Generative Artificial Intelligence in Internet Of Electric Vehicles, by Hanwen Zhang et al.
The Roles of Generative Artificial Intelligence in Internet of Electric Vehicles
by Hanwen Zhang, Dusit Niyato, Wei Zhang, Changyuan Zhao, Hongyang Du, Abbas Jamalipour, Sumei Sun, Yiyang Pei
First submitted to arxiv on: 24 Sep 2024
Categories
- Main: Machine Learning (cs.LG)
- Secondary: Artificial Intelligence (cs.AI); Emerging Technologies (cs.ET)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary The paper explores the potential applications of generative artificial intelligence (GenAI) in the electric vehicle (EV) ecosystem, specifically addressing challenges in charging management and cyber-attack prevention. The authors categorize GenAI for Internet of Electric Vehicles (IoEV) into four layers: EV’s battery layer, individual EV layer, smart grid layer, and security layer. Techniques used in each layer are introduced, along with a summary of public datasets available for training models. Recommendations for future directions are provided. This survey serves as a valuable resource for researchers and practitioners, highlighting design and implementation challenges within each layer. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary The paper is about how artificial intelligence can help make electric vehicles better. It looks at four different ways AI can be used to improve the EV system: making battery decisions, managing individual cars, smart grids, and keeping the system safe from hackers. The authors explain which techniques are being used in each area and list some public data that can be used to train these AI models. They also give suggestions for what researchers should focus on next. |
