A Risk Management Method for the Whole Route of Ferry Vehicles Based on Machine Recognition

Abstract

In response to the current information acquisition methods in the safety management process of crossing transportation vehicles, backwardness of backwardness, large manpower and material consumption, and video surveillance resources are not fully utilized, this article promotes the in -depth integration of artificial intelligence machine vision technology with the ferry business through the automatic analysis and processing technology of monitoring videos. It realizes the real-time monitoring of the operating status of the ferry vehicle and the refined control of dangerous events, providing new means for the operation monitoring of crossing vehicles, and effectively supporting the high -quality development of ferry transportation.