Record Details

Data for: Rotorcraft Landing Sites – An AI-Based Identification System

Harvard Dataverse (Africa Rice Center, Bioversity International, CCAFS, CIAT, IFPRI, IRRI and WorldFish)

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Title Data for: Rotorcraft Landing Sites – An AI-Based Identification System
 
Identifier https://doi.org/10.7910/DVN/4L6BQW
 
Creator Ghulam Rasool
Mohammad Jalayer
Nidhal Bouaynaya
David Specht
 
Publisher Harvard Dataverse
 
Description 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. This project generated an AI-based algorithm that will automate the process of identification of landing sites such as helipads and heliports from video data as well as satellite images for rotorcrafts.
 
Subject Engineering
 
Contributor Stiesi, Ryan