Frequent emergencies occur in inland rivers

lakes

and coastal waters in China. Traditional manual water rescue operations are greatly constrained by harsh hydrological and weather conditions

with shortcomings such as high risk of casualties and low search and rescue efficiency. Against the backdrop of the industrial application of artificial intelligence and multi-sensor technology

intelligent unmanned surface vessels have become important equipment for water emergency response. Based on questionnaire survey data and project simulation test results

from the perspective of emergency management

this paper sorts out the coupling logic of AI-empowered unmanned surface vessel rescue

analyzes the practical shortcomings of current autonomous rescue in environmental perception

intelligent decision-making

and supporting systems

and proposes practical optimization countermeasures from four dimensions: perception optimization

algorithm iteration

system improvement

and multi-party collaboration

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. The research results can provide practical references for the transformation of small and medium-sized rescue unmanned surface vessels and the upgrading of grassroots maritime emergency equipment.