Navigation Safety Monitoring System of Ship Bridge Area Based on Convolution Neural Network

Abstract

The construction of bridge makes the traffic across the river more smooth, but the existence of bridge piers also causes certain obstacles to the navigation of ships in the bridge area. The existing research results show that: when the ship is sailing in the bridge area, the existence of piers changes the original flow structure of the river, makes the flow pattern of the bridge area more complex, causes the ship navigation more unpredictable, and then causes the ship collision accident. In this paper, through the convolution neural network technology for ship image recognition, through the establishment of the height limit system and super height detection system, the two subsystems can sense the sensitive information of ship height, and combined with the actual situation of selective data collection, finally, the simulation experiment of the height monitoring system and water level monitoring system.