What is it about?
Drones are becoming more common, but accidents happen due to system failures, loss of control, and other issues. The National Transportation Safety Board (NTSB) records these incidents, but their reports lack a dedicated category for drone accidents. Our research uses artificial intelligence (AI) to analyze and classify UAV accident reports from 2006 to 2023. By applying natural language processing and data visualization, we identified the most common accident causes and trends. This AI-driven approach helps improve drone safety and supports better policies.
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Why is it important?
This study uses AI-based text analysis to categorize UAV accident reports from the NTSB. The research not only automates classification but also uncovers patterns in accident causes and locations. By visualizing this data, we provide insights that can enhance drone safety policies and regulations. As drones become more integrated into airspace, this research offers a timely contribution to improving UAV accident analysis and prevention.
Perspectives
Working on this study allowed us to combine our interests in aviation safety and artificial intelligence. The project reinforced how AI can streamline complex data analysis, making accident reports more useful for researchers and regulators. We hope this research encourages further collaboration between AI and aviation safety experts to enhance UAV operations.
Eugene Pik
Mevocopter Aerospace
Read the Original
This page is a summary of: Utilizing artificial intelligence for National Transportation Safety Board unmanned aerial vehicle accident analysis and categorization, International Journal of AI for Materials and Design, February 2025, Inno Science Press,
DOI: 10.36922/ijamd.8544.
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