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 v...
Saved in:
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-05-01
|
| Series: | Applied Sciences |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2076-3417/15/11/6123 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Summary: | 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. |
|---|---|
| ISSN: | 2076-3417 |