Monitoring Risks of Tower Crane Operations Using Computer Vision and Deep Learning Techniques, M.Sc. Thesis Sharif University of Technology ; Alvanchi, Amin (Supervisor)
Abstract
The utilization of tower cranes at construction sites presents numerous inherent risks. These cranes are commonly employed for lifting heavy loads, which carry the potential hazard of accidental falls. Simultaneously, workers may inadvertently overlook overhead dangers while focusing on their tasks. To mitigate these risks, laws in many countries explicitly prohibit individuals from occupying the vicinity directly beneath suspended loads, known as the fall zone. Such measures are vital to safeguard against the peril of heavy loads plummeting onto people. However, existing studies have not offered a comprehensive and efficient approach to identify crane load fall zone. To address this gap,...
Cataloging briefMonitoring Risks of Tower Crane Operations Using Computer Vision and Deep Learning Techniques, M.Sc. Thesis Sharif University of Technology ; Alvanchi, Amin (Supervisor)
Abstract
The utilization of tower cranes at construction sites presents numerous inherent risks. These cranes are commonly employed for lifting heavy loads, which carry the potential hazard of accidental falls. Simultaneously, workers may inadvertently overlook overhead dangers while focusing on their tasks. To mitigate these risks, laws in many countries explicitly prohibit individuals from occupying the vicinity directly beneath suspended loads, known as the fall zone. Such measures are vital to safeguard against the peril of heavy loads plummeting onto people. However, existing studies have not offered a comprehensive and efficient approach to identify crane load fall zone. To address this gap,...
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