In IoT-based underwater acoustic sensor networks (IoT-UASNs), critical challenges, such as inadequate node authentication mechanisms, unpredictable network topology, and ineffective localized node identification significantly hinder network performance. These challenges adversely impact node localization, route requests (RREQs) reconstruction at the beacon level, and lead to increased routing overhead, end-to-end delays, and unreliable data forwarding, thereby compromising underwater communication in critical areas of interest. Achieving reliable and efficient data transmission to sonobuoys while maintaining an optimal packet delivery ratio for localized nodes remains a significant priority. However, existing communication schemes often overlook the importance of authentication mechanisms, such as blockchain, in ensuring secure and efficient localization. Although previous research has focused mainly on generic localization strategies, the role of beacon-based localization, a key component in the formation of underwater networks, has been largely neglected. Despite the potential integration of beacon nodes with emerging technologies, such as blockchain, uncertainties persist about their ability to ensure secure underwater localization. This article addresses the pressing need to enhance the localization framework in AODV-based underwater networks by improving data delivery, optimizing RREQ and RREP processes, and minimizing both end-to-end delays and localization errors, thus paving the way for more reliable and secure underwater communication systems. In order to address these challenges, we first introduce a hybrid underwater localization communication framework based on the use of blockchain technology along with the proposed scheme, which is geomatric distance-based communication-based localization routing (CGDBLR). To establish the performance of this framework, we employ various node configurations and speeds with comparative experiments with state-of-the-art techniques. Our results show significant performance improvements for multiple parameters when integrating the blockchain in this context.

This research aims to design a smart parking system using cloud and Internet of Things (IoT) technologies to improve the process of finding parking spaces in urban areas. The proposed system utilizes sensors and microcontrollers in each parking space to provide real-time data to users through a mobile application. The primary objective of our research is to address issues, such as time-consuming manual searches for parking spaces and reduce traffic congestion. This research suggests a system of reliable smart ultra-sonic sensors connected to a microcontroller for easy and remote parking automation. Users can select a parking space by clicking on the available slot in the mobile application. Additionally, the mobile application informs users about empty spots. This smart parking system can be implemented on both small and large-scale models, and the results suggest that it effectively replicates traditional automobile parking, with the added convenience of a mobile application, in urban areas.

The research on underwater wireless sensor networks (UWSNs) has grown considerably in recent years where the main focus remains to develop a reliable communication protocol to overcome its challenges between various underwater sensing devices. The main purpose of UWSNs is to provide a low cost and an unmanned data collection system for a range of applications such as offshore exploration, pollution monitoring, oil and gas pipeline monitoring, surveillance, etc. One of the common types of UWSNs is linear sensor network (LSN), which speciall targets monitoring the underwater oil and gas pipelines. Under this application, in most of the previously proposed works, networks are deployed without considering the heterogeneity and capacity of the various sensor nodes. This negligence leads to the problem of inefficient data delivery from the sensor nodes deployed on the pipeline to the surface sinks. In addition, the existing path planning algorithms do not consider the network coverage of heterogeneous sensor nodes.

Non Orthogonal Multiple Access (NOMA) has become one of the prospective candidates for upcoming 5thgeneration Cellular network standard. Multicarrier NOMA (MC-NOMA) is a kind of hybrid NOMA, where, Orthogonal Frequency Division Multiple Access (OFDMA) may be employed to achieve higher capacity. However, MC-NOMA scheme based on OFDMA face the problem of higher Peak-to-Average Power Ratio (PAPR). The high PAPR reduces both energy and spectral efficiency of the MC-NOMA scheme. Therefore, in this paper, a new Finite Impulse Response (FIR) filtering based Zadoff-Chu Matrix Transform (ZCMT) precoded uplink MC-NOMA scheme is presented to reduce higher PAPR. MATLAB® simulations demonstrate that, the proposed filter based ZCMT precoded uplink MC-NOMA scheme outperform the ZCMT precoded uplink MC-NOMA schemes without filtering, uplink Single Carrier NOMA (SC-NOMA) schemes and conventional uplink MC-NOMA schemes available in the literature.

With the advancements of acoustic modem technology that supports better data rates with reliable communications, current research focuses on algorithms those can support such technology in a better way. During the last two decades, many protocols suggested in order to handle the adverse environment of underwater communications. This continued research results in improved performance as compare to initial communication systems. But still underwater issues like limited bandwidth, high propagation delays and 3-D topology as well as power constraints of the sensor nodes are challenges for the successful routings. A series of survey papers provide an excellent comparison of such algorithms and different networking challenges during the current decade, but still a lot left to investigate. In this paper we will explore the developments of some of the important routing algorithms, and a survey with different comparisons, those have been proposed for the partially connected underwater environments. In addition, at the end we will give some future directions, which can be helpful in order to construct the algorithms for such environments.