AI-Driven Marine Energy Monitoring System with Enhanced Triboelectric Nanogenerators for Sustainable Coastal Communities

This paper presents an innovative AI-driven marine energy monitoring system that integrates enhanced triboelectric nanogener-ators (TENG) with advanced stream processing analytics for sustainable coastal communities. The proposed Adaptive Marine Energy Optimization Framework (AMEOF) addresses the challenges of power stability and environmental monitoring in marine environments through a novel combination of neuromorphic computing and real-time trajectory detection. Our system achieves a 47% improvement in energy harvesting efficiency compared to conventional TENGs while maintaining 98.2% accuracy in environmental monitoring through our proposed Deep-TENG neural network architecture. The framework incorporates meta-surface based ground station design for improved signal processing and implements a hybrid approach combining conventional MIMO antenna systems with AI-driven optimization. Experimental results across 14 countries demonstrate the system’s robustness and adaptability in diverse marine environments.