Article

Artificial Intelligence-Powered Underwater Communication and Sensing Networks

Anita GehlotUttaranchal University,Department of Electronics & Communication Engineering Uttaranchal Institute of Technology,Dehradun,India,248007N. EsanmurodovaNational Research University,Tashkent Institute of Irrigation and Agricultural Mechanization Engineers,Tashkent,UzbekistanMohammed Al‐FarouniThe Islamic University,Najaf,IraqShruti AgrawalIES College of Technology,Department of Computer Science & Engineering,Bhopal,Madhya Pradesh,India,462044Anjani Kumar RaiGLA University,Department of CEA,Mathura,IndiaM. PreethaPrince Shri Venkateshwara Padmavathy Engineering College,Chennai,IndiaJajimoggala Sravanthi

2023en

ABI

Abstract

Ocean-related activities including ocean exploration, underwater surveillance, and environmental monitoring all depend on underwater communication. The peculiar characteristics of the underwater environment make it difficult to transfer information even with advances in underwater communication technology. By enabling the use of natural language for communication, natural language processing (NLP) techniques have the potential to increase the effectiveness and dependability of underwater communication. Huge volumes of data may be analysed using deep learning, which can also be used to spot patterns and make predictions. In order to improve the capabilities of underwater communication systems, this article suggests combining NLP and deep learning approaches.

Topics

Underwater Vehicles and Communication Systems

Identifiers

DOI: 10.1109/icteasd57136.2023.10585251

Citations and references

Cited by 016 references

Metrics — AkademScholar · Coming soon