AI Training Data Management for Reliable Autonomous Vehicles Using Hashgraph

Autonomous vehicles have attracted considerable attention from researchers and organizations, with artificial intelligence (AI) playing a key role in this technology. For AI models in autonomous vehicles to be reliable, the integrity of the training data is crucial, resulting in the development of various blockchain-based management systems. However, conventional blockchain systems incur significant time delays when processing training data transactions, posing challenges in autonomous vehicle environments that require real-time processing. In this study, we propose a hashgraph-based training data management system for trusted AI. To validate our system, we conducted simulations using the CARLA simulator and compared its performance to a conventional blockchain-based system. The simulation results show that Hedera achieved significantly lower latencies and better scalability than Ethereum, confirming its suitability for secure and efficient AI data verification in autonomous systems.

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Publication Details

Journal
Applied Sciences
Published
2025-05-29
DOI
https://doi.org/10.3390/app15116123
Primary Topic
Blockchain Technology Applications and Security
Type
article
Field-Weighted Citation Impact
0.00

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article

AI Training Data Management for Reliable Autonomous Vehicles Using Hashgraph

Y H Suh, Young-Hoon Park, Yi-Hsiang Chung
Applied Sciences
Blockchain Technology Applications and Security
article

AI Training Data Management for Reliable Autonomous Vehicles Using Hashgraph

Y H Suh, Young-Hoon Park, Yi-Hsiang Chung
article en

Abstract

Autonomous vehicles have attracted considerable attention from researchers and organizations, with artificial intelligence (AI) playing a key role in this technology. For AI models in autonomous vehicles to be reliable, the integrity of the training data is crucial, resulting in the development of various blockchain-based management systems. However, conventional blockchain systems incur significant time delays when processing training data transactions, posing challenges in autonomous vehicle environments that require real-time processing. In this study, we propose a hashgraph-based training data management system for trusted AI. To validate our system, we conducted simulations using the CARLA simulator and compared its performance to a conventional blockchain-based system. The simulation results show that Hedera achieved significantly lower latencies and better scalability than Ethereum, confirming its suitability for secure and efficient AI data verification in autonomous systems.

Applied SciencesVol. 15(11)
Sookmyung Women's University (KR)
Iran Telecommunication Research Center, Ministry of Science and ICT, South Korea, Institute for Information and Communications Technology Promotion
Openalex Percentile: Top 83%
Blockchain Technology Applications and Security
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