UWSN: A Novel Artificial Intelligence (AI) enabled Scheme to Improve Security and Energy Efficiency over Underwater Wireless Sensor Networks

Underwater Wireless Sensor Networks (UWSNs) are critical for monitoring and managing marine environments, supporting applications in environmental science, defense, and resource exploration. This study presents an innovative AIenabled scheme for improving security and energy efficiency in Underwater Wireless Sensor Networks (UWSNs). By incorporating artificial intelligence, the proposed AI-UWSN protocol dynamically adapts to environmental and network conditions, enhancing key performance metrics like energy consumption, packet delivery ratio (PDR), latency, and network lifetime. The AI-UWSN achieved an average energy consumption of 146J, which is 24% lower than conventional protocols, extending the network lifetime to 1067 hours, compared to 722 hours in existing methods. Additionally, the protocol's intelligent routing increased PDR to 89%, significantly reducing data loss, and maintained an average latency of 108ms, 15% lower than alternative protocols. These improvements result from AI-based routing and clustering strategies, which optimize data aggregation and power usage, extending the network's functionality even in high-density, high-traffic environments.