Smoke Detection of Marine Engine Room Based on a Machine Vision Model (CWC-Yolov5s)

• Published in: Journal of marine science and engineering Vol. 11; no. 8; p. 1564
• Main Authors: Zou, Yongjiu, Zhang, Jinqiu, Du, Taili, Jiang, Xingjia, Wang, Hao, Zhang, Peng, Zhang, Yuewen, Sun, Peiting
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01.08.2023
• Subjects: Accuracy; Algorithms; Codes; Computer vision; Convolution; Crew; Datasets; Deep learning; Detection; Engine rooms; Engines; Fires; Forest & brush fires; Image enhancement; improved YOLOv5s model; intelligent ship; Internet of Things; Machine vision; Marine accidents; Marine engines; Model accuracy; Object recognition; Regression models; Research methodology; Smoke; smoke detection; Statistical methods; Vision systems; Wavelet transforms

According to statistics, about 70% of ship fire accidents occur in the engine room, due to the complex internal structure and various combustible materials. Once a fire occurs, it is difficult to extinguish and significantly impacts the crew’s life and property. Therefore, it is urgent to design a m...