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| Main Authors: | , , , |
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| Format: | Preprint |
| Published: |
2024
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2409.16968 |
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| _version_ | 1866909748344913920 |
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| author | Redondo, Jeffrey Aslam, Nauman Zhang, Juan Yuan, Zhenhui |
| author_facet | Redondo, Jeffrey Aslam, Nauman Zhang, Juan Yuan, Zhenhui |
| contents | Nowadays, many machine learning (ML) solutions to improve the wireless standard IEEE802.11p for Vehicular Adhoc Network (VANET) are commonly evaluated in the simulated world. At the same time, this approach could be cost-effective compared to real-world testing due to the high cost of vehicles. There is a risk of unexpected outcomes when these solutions are implemented in the real world, potentially leading to wasted resources. To mitigate this challenge, the hardware-in-the-loop is the way to move forward as it enables the opportunity to test in the real world and simulated worlds together. Therefore, we have developed what we believe is the pioneering hardware-in-the-loop for testing artificial intelligence, multiple services, and HD map data (LiDAR), in both simulated and real-world settings. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2409_16968 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Bridge to Real Environment with Hardware-in-the-loop for Wireless Artificial Intelligence Paradigms Redondo, Jeffrey Aslam, Nauman Zhang, Juan Yuan, Zhenhui Machine Learning Networking and Internet Architecture Signal Processing Nowadays, many machine learning (ML) solutions to improve the wireless standard IEEE802.11p for Vehicular Adhoc Network (VANET) are commonly evaluated in the simulated world. At the same time, this approach could be cost-effective compared to real-world testing due to the high cost of vehicles. There is a risk of unexpected outcomes when these solutions are implemented in the real world, potentially leading to wasted resources. To mitigate this challenge, the hardware-in-the-loop is the way to move forward as it enables the opportunity to test in the real world and simulated worlds together. Therefore, we have developed what we believe is the pioneering hardware-in-the-loop for testing artificial intelligence, multiple services, and HD map data (LiDAR), in both simulated and real-world settings. |
| title | Bridge to Real Environment with Hardware-in-the-loop for Wireless Artificial Intelligence Paradigms |
| topic | Machine Learning Networking and Internet Architecture Signal Processing |
| url | https://arxiv.org/abs/2409.16968 |