Innovative strategy and practice of using underwater robot for marine cable inspection and operation and maintenance

Abstract

This research explores underwater robot applications in marine cable inspection and maintenance with solutions to accuracy, reliability, and efficiency challenges. Current methods using human divers and remotely operated vehicles (ROVs) are expensive, time-consuming, and involve safety hazards. The suggested AI-based robotic system incorporates sensor technology, predictive maintenance, and statistical validation to maximize marine cable inspections. A quantitative research method was employed, surveying data from 400 Marine Engineers and Underwater Robotics Specialists. Statistical analysis, such as reliability analysis, regression model, and hypothesis testing, determined the influence of technology adoption, environmental aspects, and predictive maintenance on inspection accuracy and cost savings. Model fit was confirmed through CFI $=0.94$, RMSEA $=0.047$, and $\mathrm{SRMR}=0.052$. Results show that Maintenance Strategy & Cost Reduction $(\beta =0.55,p<0.01)$ is most influential. The research assures that AI-enhanced underwater robots provide a cost-efficient, guaranteed substitute to conventional approaches, promoting efficiency, safety, and long-term sustainability in marine cable operations.