| Project Overview | This B.Tech Aerospace / Aeronautical Engineering project is based on the recent research direction 'Aircraft Landing Time Prediction with Deep Learning on Trajectory Images'. The project focuses on applying artificial intelligence, machine learning, deep learning, computer vision, reinforcement learning, surrogate modelling, or RAG-style intelligent assistance to the Aircraft Design Projects area. Students can use the linked 2023-onward research paper/source as the academic base, then convert it into an implementation-focused final-year project with a simplified dataset, simulation model, Python workflow, dashboard, or prototype demonstration. |
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| Research Paper Title | Aircraft Landing Time Prediction with Deep Learning on Trajectory Images |
| Research Paper / PDF Link | Open Paper / PDF |
| Year | 2024 |
| Project Area | Aircraft Design Projects |
| Project Type | Deep Learning + Aircraft Operations |
| Required Tools / Software | Python, Scikit-learn, PyTorch/TensorFlow, OpenVSP optional, CAD data, Streamlit |
| Main Features / Working Principle | Convert aircraft trajectory data into image-like representations and predict landing time/classes |
| Expected Output | A trajectory-based landing-time prediction prototype |
| Possible Add-ons | Add map visualization and delay-risk dashboard |
| Get Help | Get Help on WhatsApp
Message: Hi FE, I need help with "Aircraft Landing Time Prediction with Deep Learning on Trajectory Images" in "Aerospace / Aeronautical Engineering" |
This B.Tech aerospace project resource helps students connect a recent AI-based research direction with a practical implementation plan, tools, expected output, and possible extensions.