### Fundamentals and Motivations
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As per Section 1.1 and Table 1, many researchers developed their research focusing on energy-efficient MAC and routing protocols of UIoT networks; for example, articles discussed routing protocols [3; 4; 5], and [10; 11; 12; 13; 14; 15; 16], articles discussed MAC protocols [6; 7; 8; 9], and [17; 18; 19; 20; 21]. Furthermore, as per Table 2, several researchers provided surveys concerning the existing energy consumption and energy-saving issues of current UIoT system. Based on Section 1.1, most of the energy optimization techniques for UIoT networks are set up using a simulation environment, and also, the researchers and developers focused only on building energy-efficient MAC and routing protocols for UIoT networks, these techniques cannot be utilized as the best solution for energy-optimization in UIoT networks; due to the lack of field experiments, high cost, design issues, development, and management of devices in constrained UIoT networks. Therefore, since 2010, several researchers have been focused on building numerous energy optimization techniques for UIoT applications with field experiments [22; 23; 24; 25; 26; 27; 28; 29; 30; 31; 32; 33; 34; 35; 36; 37; 38; 39; 40; 41; 42; 43; 44; 45; 46; 47; 48], for example, underwater wireless power transfer for maritime applications [22], battery replacement approach for UIoT applications [23], automatic recharge techniques for UIoT networks [24], battery-free sensor nodes for UIoT networks [25], solar charging system for AUVs [26], artificial intelligence and machine learning-based energy optimization techniques for UIoT applications [27], etc. However, due to the technical limitations of UIoT networks, such as attenuation, channel noise, node mobility, and dynamic topology formation, etc., the battery life of UIoT devices can still be reduced. In effect, this can affect the network lifetime and damage the battery. Even though several researchers have provided their existing surveys concerning energy-efficient MAC and routing protocols of UIoT networks [3; 4; 5; 6; 7; 8; 9; 10; 11; 12; 13; 14; 15; 16; 17; 18; 19; 20; 21], and recent surveys based on Table 2 [49; 50; 51; 52; 53; 54; 55; 56], it is necessary to include communication technologies, state-of-the-art articles based on real field experiments, and future research directions for delivering energy-optimized communication for UIoT networks. \begin{table}
\begin{tabular}{p{113.8 pt} p{113.8 pt} p{113.8 pt} p{113.8 pt}} \hline \hline
**Author and Ref.** & **Authors** & **Authors** & **Authors** & **Authors** \\ \hline [PERSON] et al. in 2016 [49] & & & Focused on the study of energy-efficient MAC and routing protocols of underwater wireless sensor networks & \\ \hline [PERSON] at al. in 2017 [50] & & Focused on analyzing energy-efficient routing protocols of underwater communication & \\ \hline [PERSON] et al. in 2018 [51] & & Focused on opportunistic routing for underwater acoustic communication technology & \\ \hline [PERSON] et al. in 2018 [52] & & Focused on the analysis of various routing protocols of underwater sensor networks, its research challenges, and provides the solutions to improve the performance on concerning issues such as propagation delay, limited battery, and node mobility, etc. & \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Summary of recent surveys concerning energy-optimization techniques in UIoT.