Investigation of Unsafe Construction Site Conditions Using Deep Learning Algorithms Using Unmanned Aerial Vehicles

The rapid adoption of Unmanned Aerial Vehicles (UAVs) in the construction industry has revolutionized safety, surveying, quality monitoring, and maintenance assessment. UAVs are increasingly used to prevent accidents caused by falls from heights or being struck by falling objects by ensuring workers...

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Vydané v:	Sensors (Basel, Switzerland) Ročník 24; číslo 20; s. 6737
Hlavní autori:	Kumar, Sourav, Poyyamozhi, Mukilan, Murugesan, Balasubramanian, Rajamanickam, Narayanamoorthi, Alroobaea, Roobaea, Nureldeen, Waleed
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Switzerland MDPI AG 01.10.2024 MDPI
Predmet:	Accidents Algorithms automatic detection Automation Building Compliance Construction accidents & safety Construction industry Construction workers Data mining Data processing Drone aircraft Drones Efficiency image recognition object detection Occupational health and safety Occupational safety Personal protective equipment Privacy Quality control Quality management Safety equipment Safety management Safety standards Strikes Surveillance tensor flow Trends Unmanned Aerial Vehicle Unmanned aerial vehicles unsafe site conditions Weather Workers' compensation object detection automatic detection unsafe site conditions tensor flow image recognition Unmanned Aerial Vehicle
ISSN:	1424-8220, 1424-8220
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