Rotorcraft Landing Sites – An AI-Based Identification System
The updated information about the location and type of landing sites is an essential asset for the Federal Aviation Administration (FAA) and the Department of Transportation (DOT). However, the acquisition, verification, and regular updating of information about landing sites is not an easy or straightforward task, and the lack of current and correct information on helicopter landing sites is a risk factor in several accidents and incidents involving rotorcraft. The primary goal of this proposal is to create an artificial intelligence (AI)-based system for the identification of helipads, heliports, and landing site infrastructure from various heterogeneous datasets, including video from rotorcraft, drones, satellite images, or aerial imagery, as well as textual data sources (i.e., data entered by helipad owners/operators or pilots) from other sources. The intended outcome of the project is to generate an AI algorithm that will automate the process of identification of landing sites from video data as well as satellite images. The researchers hope to achieve landing site identification accuracy equal to or higher than that of a trained human operator at a fraction of time and resources. Once developed, the AI system would allow FAA to update its databases of landing sites regularly without any delays so the information could be used by any mission, including “Helicopter Air Ambulance missions to rural communities.”
- Record URL:
Language
- English
Project
- Status: Active
- Funding: $160000
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Contract Numbers:
69A3551847102
CAIT-UTC-REG 32
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Sponsor Organizations:
Office of the Assistant Secretary for Research and Technology
University Transportation Centers Program
Department of Transportation
Washington, DC United States 20590 -
Managing Organizations:
Federal Aviation Administration
William J. Hughes Technical Center, Atlantic City International Airport
Atlantic City, NJ United States 08405New Jersey Department of Transportation
1035 Parkway Avenue
Trenton, NJ United States 08625Center for Advanced Infrastructure and Transportation
Rutgers University
100 Brett Road
Piscataway, NJ United States 08854-8058 -
Project Managers:
Johnson, Charles (Cliff)
Stott, Glenn
Szary, Patrick
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Performing Organizations:
Rowan University
College of Engineering
201 Mullica Hill Road
Glassboro, NJ United States 08028 -
Principal Investigators:
Rasool, Ghulam
Bouaynaya, Nidhal
Jalayer, Mohammad
- Start Date: 20200101
- Expected Completion Date: 20201231
- Actual Completion Date: 0
- USDOT Program: University Transportation Centers Program
Subject/Index Terms
- TRT Terms: Algorithms; Artificial intelligence; Data collection; Drones; Heliports; Location; Video
- Subject Areas: Aviation; Data and Information Technology; Terminals and Facilities;
Filing Info
- Accession Number: 01727612
- Record Type: Research project
- Source Agency: Center for Advanced Infrastructure and Transportation
- Contract Numbers: 69A3551847102, CAIT-UTC-REG 32
- Files: UTC, RIP
- Created Date: Jan 17 2020 11:06AM