The Roles of Generative Artificial Intelligence in Internet of Electric Vehicles

• URL: http://arxiv.org/abs/2409.15750v3
• Date: Thu, 14 Nov 2024 06:33:26 GMT
• Title: The Roles of Generative Artificial Intelligence in Internet of Electric Vehicles
• Authors: Hanwen Zhang, Dusit Niyato, Wei Zhang, Changyuan Zhao, Hongyang Du, Abbas Jamalipour, Sumei Sun, Yiyang Pei,
• Abstract summary: We specifically consider Internet of electric vehicles (IoEV) and we categorize GenAI for IoEV into four different layers. We introduce various GenAI techniques used in each layer of IoEV applications. Public datasets available for training the GenAI models are summarized.
• Score: 65.14115295214636
• License:
• Abstract: With the advancements of generative artificial intelligence (GenAI) models, their capabilities are expanding significantly beyond content generation and the models are increasingly being used across diverse applications. Particularly, GenAI shows great potential in addressing challenges in the electric vehicle (EV) ecosystem ranging from charging management to cyber-attack prevention. In this paper, we specifically consider Internet of electric vehicles (IoEV) and we categorize GenAI for IoEV into four different layers namely, EV's battery layer, individual EV layer, smart grid layer, and security layer. We introduce various GenAI techniques used in each layer of IoEV applications. Subsequently, public datasets available for training the GenAI models are summarized. Finally, we provide recommendations for future directions. This survey not only categorizes the applications of GenAI in IoEV across different layers but also serves as a valuable resource for researchers and practitioners by highlighting the design and implementation challenges within each layer. Furthermore, it provides a roadmap for future research directions, enabling the development of more robust and efficient IoEV systems through the integration of advanced GenAI techniques.

Related papers

• Model-based Maintenance and Evolution with GenAI: A Look into the Future [47.93555901495955]
  We argue that Generative Artificial Intelligence (GenAI) can be used as a means to address the limitations of Model-Based Engineering (MBM&E) We propose that GenAI can be used in MBM&E for: reducing engineers' learning curve, maximizing efficiency with recommendations, or serving as a reasoning tool to understand domain problems.
  arXiv  Detail & Related papers  (2024-07-09T23:13:26Z)
• Strategic Demand-Planning in Wireless Networks: Can Generative-AI Save Spectrum and Energy? [17.59973153669422]
  This article introduces the concept of strategic demand-planning through demand-labeling, demand-shaping, and demand-rescheduling. GenAI is proposed as a powerful tool to facilitate demand-shaping in wireless networks. GenAI can serve a function in saving energy and spectrum in wireless networks.
  arXiv  Detail & Related papers  (2024-07-02T14:27:06Z)
• Networking Systems for Video Anomaly Detection: A Tutorial and Survey [55.28514053969056]
  Video Anomaly Detection (VAD) is a fundamental research task within the Artificial Intelligence (AI) community. In this article, we delineate the foundational assumptions, learning frameworks, and applicable scenarios of various deep learning-driven VAD routes. We showcase our latest NSVAD research in industrial IoT and smart cities, along with an end-cloud collaborative architecture for deployable NSVAD.
  arXiv  Detail & Related papers  (2024-05-16T02:00:44Z)
• Integration of Mixture of Experts and Multimodal Generative AI in Internet of Vehicles: A Survey [82.84057882105931]
  Generative AI (GAI) can enhance the cognitive, reasoning, and planning capabilities of intelligent modules in the Internet of Vehicles (IoV) We present the fundamentals of GAI, MoE, and their interplay applications in IoV. We discuss the potential integration of MoE and GAI in IoV, including distributed perception and monitoring, collaborative decision-making and planning, and generative modeling and simulation.
  arXiv  Detail & Related papers  (2024-04-25T06:22:21Z)
• Generative AI and Process Systems Engineering: The Next Frontier [0.5937280131734116]
  This article explores how emerging generative artificial intelligence (GenAI) models, such as large language models (LLMs), can enhance solution methodologies within process systems engineering (PSE) These cutting-edge GenAI models, particularly foundation models (FMs), are pre-trained on extensive, general-purpose datasets. The article identifies and discusses potential challenges in fully leveraging GenAI within PSE, including multiscale modeling, data requirements, evaluation metrics and benchmarks, and trust and safety.
  arXiv  Detail & Related papers  (2024-02-15T18:20:42Z)
• At the Dawn of Generative AI Era: A Tutorial-cum-Survey on New Frontiers in 6G Wireless Intelligence [11.847999494242387]
  Generative AI (GenAI) pertains to generative models (GMs) capable of discerning the underlying data distribution, patterns, and features of the input data. This makes GenAI a crucial asset in wireless domain wherein real-world data is often scarce, incomplete, costly to acquire, and hard to model or comprehend. We outline the central role of GMs in pioneering areas of 6G network research, including semantic/THz/near-field communications, ISAC, extremely large antenna arrays, digital twins, AI-generated content services, mobile edge computing and edge AI, adversarial ML, and trustworthy
  arXiv  Detail & Related papers  (2024-02-02T06:23:25Z)
• From Generative AI to Generative Internet of Things: Fundamentals, Framework, and Outlooks [82.964958051535]
  Generative Artificial Intelligence (GAI) possesses the capabilities of generating realistic data and facilitating advanced decision-making. By integrating GAI into modern Internet of Things (IoT), Generative Internet of Things (GIoT) is emerging and holds immense potential to revolutionize various aspects of society.
  arXiv  Detail & Related papers  (2023-10-27T02:58:11Z)
• Large Generative AI Models for Telecom: The Next Big Thing? [7.36678071967351]
  Large GenAI models are envisioned to open up a new era of autonomous wireless networks. In this article, we aim to unfold the opportunities that can be reaped from integrating large GenAI models into the Telecom domain.
  arXiv  Detail & Related papers  (2023-06-17T03:45:00Z)
• Artificial Intelligence Aided Next-Generation Networks Relying on UAVs [140.42435857856455]
  Artificial intelligence (AI) assisted unmanned aerial vehicle (UAV) aided next-generation networking is proposed for dynamic environments. In the AI-enabled UAV-aided wireless networks (UAWN), multiple UAVs are employed as aerial base stations, which are capable of rapidly adapting to the dynamic environment. As a benefit of the AI framework, several challenges of conventional UAWN may be circumvented, leading to enhanced network performance, improved reliability and agile adaptivity.
  arXiv  Detail & Related papers  (2020-01-28T15:10:22Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.