Page 11 - IJAMD-2-1

International Journal of AI for
Materials and Design
Utilizing AI for NTSB UAV accident categorization

Figure 2. Interactive map of the UAV accidents 23

Figure 3. Accidents per year by category

narrative sections of reports to identify underlying comprehensive safety frameworks. Collaboration with
causes and contributing factors more accurately. Machine regulatory bodies and industry stakeholders will be vital
learning algorithms should be developed and refined to in implementing these advanced technologies effectively.
classify accident scenarios and predict potential risks. Future work will involve a larger number of NTSB reports
These algorithms can enhance proactive safety measures to enable robust statistical analysis. Future research can
by providing early warnings based on historical data and enhance reliability by ensuring consistent results across
emerging trends. Interdisciplinary research combining different initial conditions and demonstrating model
expertise from aviation, AI, and data science can lead to convergence as more data is added, confirming stability

Volume 2 Issue 1 (2025) 5 doi: 10.36922/ijamd.8544