基于YOLOv8的消火栓状态在线监测与预警OA

Fire hydrants play a crucial role in the railway fire protection system.However,relevant monitoring devices are only suitable for single specific tasks,and their monitoring accuracy is easily affected by the railway envi-ronment,imposing high requirements on the performance of hardware devices.In view of this problem,this study proposes a research method for online monitoring and early warning of fire hydrant status based on YOLOv8(You Only Look Once version 8).CPU(Central Processing Unit)-GPU(Graphics Processing Unit)heterogeneous computing and modified activation functions are adopted to ensure that the device can achieve acceleration under the same accu-racy,with relatively low requirements for edge hardware performance.The CPU-GPU heterogeneous strategy is used to optimize the image detection frame rate,and the H-Swish function is applied to improve the computational efficien-cy of the activation function,enhancing the model's fitting and expression capabilities.Experimental results show that compared with traditional methods,the proposed method accelerates the detection speed by 1.85 times,increases the detection frame rate by approximately 16.5%,and achieves an accuracy of 98.1%,meeting the requirements of practical applications.