Integrating real-time pose estimation and PPE detection with cutting-edge deep learning for enhanced safety and rescue operations in the mining industry

• Published in: Neurocomputing (Amsterdam) Vol. 618; p. 129080
• Main Authors: Imam, Mohamed, Baïna, Karim, Tabii, Youness, Ressami, El Mostafa, Adlaoui, Youssef, Boufousse, Soukaina, Benzakour, Intissar, Abdelwahed, El Hassan
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 14.02.2025
• Subjects: Deep learning; Human pose estimation (HPE); Machine learning; Miners’ safety; Personal Protective Equipment (PPE); Underground mines; Underground mines; Deep learning; Human pose estimation (HPE); Personal Protective Equipment (PPE); Miners’ safety; Machine learning

The dynamic and often hazardous environments of mines necessitate advanced safety protocols, particularly in PPE compliance and emergency response. This study leverages cutting-edge pose estimation and object detection technologies to enhance miner safety by focusing on two primary goals: developing...