An intelligent SCADA-integrated deep learning framework for bird-safe offshore wind farm operation
Yara A. Sultan, Ahmed Sameh, Samah A. Gamel · 2026
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Description
Yara A Sultan, Ahmed Sameh, and Samah A Gamel present a 2026 framework for running offshore wind farms without harming birds. Turbines can strike migrating birds, and older safeguards like radar or alarms often react late or cry wolf. Their system pairs a deep learning bird spotter with the farm's control system.
The spotter was trained on more than 90,000 images covering 525 bird species. It sorted birds with accuracy above 99 percent in tests, beating four standard methods. In simulation, it answered in under 30 milliseconds and the control system acted within 40. The model sorts birds by species and judges how close they are, so turbines can respond by risk zone. The authors warn that real sea trials are still needed.
Catalog record
| CREATOR | Yara A. Sultan, Ahmed Sameh, Samah A. Gamel |
|---|---|
| YEAR | 2026 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 55543 |
| LICENSE | https://creativecommons.org/licenses/by/4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |