Evaluation of IIOT based Pd-MaaS using CNN with Ensemble Subspace Discriminate – for Indian Ship Building in Maritime Industry

Abstract

Indian shipbuilding has a long history in the maritime industry dating back to the origin of civilization. India's shipbuilding sector is primarily concentrated in its coastal regions. Due to capacity constraints and decreased shipbuilding prices in emerging nations, shipbuilding activities has changed. This has created fresh opportunities for the Indian shipbuilding industry. The prospects for the Indian shipbuilding sector are improved by rising global trade and strong need for modern boats. This study investigates the use of Predictive Maintenance as a Service on the Industrial Internet of Things (IIoT-PdMaaS). Artificial intelligence (AI) in the maritime industry has numerous major benefits, including improved decision-making analysis, automation, security, route planning, and increased efficiency. So, Pd-MaaS using IIOT (Convolution neural network (CNN) with Ensemble Boosted Tree Classifier) framework was developed in this study. This research shows 88.3% accuracy of CNN output for confusion matrix implying a positive connection with our proposed model for Indian ship building industry