Abstract

The underwater internet of things (UIoT) has emerged as a booming technology in today’s digital world due to the enhancement of a wide range of underwater applications concerning ocean exploration, deep-sea monitoring, underwater surveillance, diver network monitoring, location and object tracking, etc. Generally, acoustic, infrared (IR), visible light (VL), radiofrequency (RF), and magnet induction (MI) are used as the medium of communication in order to transfer information among digitally linked underwater devices. However, each communication medium has its advantages and limitations: for example, the acoustic communication medium is suitable for long-range data transmission but has challenges such as narrow bandwidth, long delay, and high cost, etc., and the optical medium is suitable for short-range data transmission but has challenges such as high attenuation, and optical scattering due to water particles, etc. Furthermore, UIoT devices are operated using batteries with limited capacity and high energy consumption; hence, energy consumption is considered as one of the most significant challenges in UIoT networks. Therefore, to support reliable and energy-efficient communication in UIoT networks, it is necessary to adopt robust energy optimization techniques for UIoT networks. Hence, this paper focuses on identifying the various issues concerning energy optimization in the underwater internet of things and state-of-the-art contributions relevant to inducement techniques of energy optimization in the underwater internet of things; that provides a systematic literature review (SLR) on various power-saving and optimization techniques of UIoT networks since 2010, along with core applications, and research gaps. Finally, future directions are proposed based on the analysis of various energy optimization issues and techniques of UIoT networks. This research contributes much to the profit of researchers and developers to build smart, energy-efficient, auto-rechargeable, and battery-less communication systems for UIoT networks.

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