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An overview of the internet of underwater things

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Abstract

Approximately 71% of the Earth's surface is covered by ocean, a continuous body of water that is customarily divided into several principal oceans and smaller seas. Ocean temperatures determine climate and wind patterns that affect life on land. Freshwater in lakes and rivers covers less than 1%. Its contamination seriously damages ecosystems. The Internet of Underwater Things (IoUT) is defined as a world-wide network of smart interconnected underwater objects that enables to monitor vast unexplored water areas. The purpose of this paper is to analyze how to benefit from the IoUT to learn from, exploit and preserve the natural underwater resources. In this paper, the IoUT is introduced and its main differences with respect to the Internet of Things (IoT) are outlined. Furthermore, the proposed IoUT architecture is described. Important application scenarios that illustrate the interaction of IoUT components have been proposed. Critical challenges have been identified and addressed.

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... Thus, it is of paramount importance to discover more about the ocean. The concept of Internet of Underwater Things (IoUT) has become a powerful technology to enable smart oceans and explore vast ocean areas (Domingo, 2012). IoUT system is a technical revolutionary step of computing and communication. ...
... The aim of this project is to extend the concept of IoUT for marine environment for unprecedented monitoring. Military is also focusing to build military internet of (Domingo, 2012).This study proposes IoUT to preserve natural underwater resources. Authors have identified and addressed potential applications and critical challenges for IoUT. ...
... IoT has also empowered the concept of next generation underwater wireless sensor network named as IoUT. The term "IoUT" was first introduced by Domigo in an article titled "An Overview of the Internet of Underwater Things" in 2012 (Domingo, 2012). Similar to the concept of IoT, IoUT is defined as a world-wide interconnected network of digitally identified underwater objects capable of sensing, processing and transferring information to remote base stations. ...
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The innovative concept of Internet of Underwater Things (IoUT) has a huge impact in different sectors including a small scientific laboratory, to a medium sized harbor, and to monitor vast undiscovered oceans. Internet of Underwater Things (IoUT) has become a powerful technology to support various applications such as collecting real-time aquatic information, naval military applications, maritime security, natural disaster prediction and control, archaeological expeditions, oil and gas exploration , shipwrecks discovery, water contamination, marine life observation and smart Ocean. IoUT is referred as smart intricately linked underwater objects to monitor these underwater operations. The IoUT framework incorporates several underwater communication technologies based on magnetic induction, optical signals, radio signals and acoustic waves. It is an emerging communication ecosystem which can reveal a new era of research, business and naval applications. It is a novel and vibrant paradigm for the Blue Economy sector bringing the ability to communicate autonomous underwater vehicles (AUVs), sensing, actuating and transferring this data to control centers using regular internet speeds through low cost technologies. It is anticipated to support future networking systems which can bring tremendous improvement in previous generations in terms of stable networking, high coverage, massive connectivity, low latency, high data rate and low power consumption. This study introduces the possible network framework of IoUT which is naturally heterogeneous and must be flexible enough to work under unpredicted ocean conditions. In this study, we examine channel models, routing protocols, networking topologies and simulation tools. Furthermore, we discussed recent advancements in IoUT in terms of smart devices, consumer electronics, communication and role of AUVs. In addition, edge computing, optical wireless communication (OWC), data analytics, blockchain, intelligent reflecting surfaces (IRS) and machine learning were viewed as promising techniques to support IoUT. We have dedicated a complete section to applications of IoUT. Finally, numerous open research challenges and future directions were presented. We believe this survey will be helpful to aggregate the research efforts and eliminate the technical uncertainties towards breakthrough novelties of IoUT.
... It is well known that the Internet of Things (IoT) can connect ubiquitous devices and facilities with various networks to provide efficient and secure services for all applications anytime and anywhere [2,3]. With the continuous development of the wireless IoT, the concept of underwater Internet of Things (IoUT) has also been raised [4]. It is defined as "the network of smart interconnected underwater objects" [5]. ...
... As shown in Figure 1, the BTBO protocol is a protocol for centralized networks. This protocol can be applied to IoUT in data collection and many scenarios, such as aquariums, fish farms, pipeline monitoring, harbour security and so on [4]. Next, let us introduce the basic process of BTBO protocol. ...
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With the development of underwater internet, Underwater Acoustic Sensor Networks (UASNs) have become an important method for collecting marine parameters and data. The Medium Access Control (MAC) protocol is the underlying infrastructure of UASNs. It directly affects the utilization of the underwater acoustic channel and the overall performance of the network. The ALOHA protocol is the basis of the random accessing protocols. It freely accesses the channel, so the collision between data packets is very serious. To this end, this paper proposes a Backoff‐Toleration‐Based Opportunistic (BTBO) protocol. In this protocol, each sensor node opportunistically learns by backoffing tolerantly, and finds the optimal transmission time respectively to transmit the data packet. Simulation results show that the BTBO protocol has better throughput and average end‐to‐end delay. At the same time, the authors added adaptive design to the dynamic topology networks in the UASNs. The simulation results show that the protocol can effectively alleviate these problems and improve performance.
... Advancement in sensing, communication and robotics technologies have enabled the development of the lowcost AUVs-assisted Underwater Acoustic Sensor Network (UASN) [1][2][3]. It can be used for various applications such as deep ocean exploration, monitoring and target tracking in the marine environment, development of the offshore oil field, observation of the marine meteorological parameters etc [4][5][6][7]. ...
... It can be used for various applications such as deep ocean exploration, monitoring and target tracking in the marine environment, development of the offshore oil field, observation of the marine meteorological parameters etc [4][5][6][7]. AUVs-assisted UASN is a multi-hop distributed and self-organizing network which consist of a set of Underwater Sensors Nodes (USNs) and a set of Autonomous Underwater Vehicles (AUVs) for data collection from the deployed USNs [1][2][3][4][5]. Each AUV connects with the Base Station (BS) at the seashore [7][8][9][10]. ...
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In the Autonomous Underwater Vehicle (AUV) based Underwater Acoustic Sensor Network (UASN), efficient data collection with minimum delay and high throughput is a fundamental research challenge. Most of the existing data collection schemes using AUVs are suffered from unbalanced energy consumption, long delay, partial coverage, and incomplete data collection problems. To overcome these problems, this paper proposed an optimized coverage-aware target node selection and trajectory planning scheme for AUVs for fast and efficient data collection in the Underwater Sensor Networks. Optimal selection of coverage-aware target nodes and trajectory planning of the multiple AUVs are proposed using Backtracking Search Optimization (BSO) technique. After deployment of the underwater sensor nodes, first, network is partitioned into a set of load balanced cluster-region. After that, optimized coverage-aware target node is selected from each cluster-region for collection of the sensed data using AUVs. For optimizing the trajectory of the AUVs, a BSO-based trajectory planning scheme is proposed with novel fitness function. The proposed scheme dispatches multiple AUVs concurrently for high availability and low delay in the data collected from the cluster-regions. Performance of the proposed scheme is evaluated and compared with some latest state-of-art existing schemes in terms of coverage ratio, total travel distance, maximum travel distance, delay, and average energy consumption. Simulation results confirm that the proposed scheme performs well and very capable in providing the fast and high availability of the sensed data collection from UASN.
... These accumulated data can be examined and serviced by the ground uphold units. 2 In order to transfer information between these nodes, different communication technologies such as radio frequency (RF) and acoustic and optical communication have been used. The use of RF is limited to a few meters due to high attenuation of seawater with the increasing frequencies. ...
Article
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The Internet of Underwater Things (IoUTs) can be considered as a potential candidate to interconnect physical devices (things) such as submarines, ships, divers, buoys, and unmanned underwater vehicles (AUVs) to collect and exchange information with each other in the ocean environment. Traditionally, sound waves have been used to transfer information between IoUTs, but due to the lack of limited bandwidth and data rate, the underwater wireless optical communication (UWOC)-based IoUTs can be considered as a viable solution. In this work, a real-time RGB image is transferred between two IoUTs using an intensity modulation direct detection (IM/DD) on–off keying (OOK) modulation scheme. To estimate the performance of the reconstructed image, structure similarity index (SSIM) and peak signal-to-noise ratio (PSNR) have been evaluated. During transmission of an image through the water, the quality of the received image degrades due to the absorption, scattering, and underwater turbulence which further limits the transmission range. Thus, to enhance the quality of the received images, two filters, that is, median and Wiener filters, have been proposed. The median filter improves the SSIM and PSNR of the reconstructed image more appropriately as compared to the Wiener filter. The results show that the proposed median filter can enhance the communication range of the UWOC point-to-point link by 100 m.
... IoUwT is a promising research area, which has seen a lot of advances in the recent years. For more information on underwater communications and IoUwT we refer to [74], [78]. ...
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Challenging environments comprise a range of scenarios, which share the fact that it is extremely difficult to establish a communication link using conventional technology due to many impairments typically associated with the propagation medium and increased signal scattering. Specifically, underwater and underground media are known to absorb electromagnetic radiation, which heavily affects the overall path loss. Industrial and disaster environments can be viewed as rich scattering environments with corresponding substantial multipath propagation leading to intersymbol interference and deterioration of signal quality. Although the challenges for the design of communication networks, and specifically the Internet of Things (IoT), in such environments are known, there is no common enabler or solution for all these applications. Reconfigurable intelligent surfaces (RISs) have been introduced to improve the signal propagation characteristics by focusing the signal power in the preferred direction, thus making the communication environment ’smart’. While the usual application of RIS is related to blockage avoidance, the very same technique can be used to reduce the effect of multipath and even partially compensate the signal absorption via passive beamforming. Due to the beneficial properties of RIS, its use in challenging environments can become the aforementioned enabler and a game changing technology. However, various aspects of RIS deployment and system design need to be addressed in order to fully benefit from this technology. In this paper, we discuss potential use cases, deployment strategies and design aspects for RIS devices in underwater IoT, underground IoT as well as Industry 4.0 and emergency networks. Furthermore, we provide a potential hardware architecture and derive the expected signal quality improvements with increasing number of RIS elements. The numerical results reveal substantial performance gains of up to 20 dB per decade. In addition, novel research challenges to be addressed in this context are described.
... The system can remotely monitor and scientifically control the environmental parameters of the planting site. In summary, with the continuous development of Internet of Things technology and wireless communication technology, wireless sensor networks are applied to agricultural production to provide technical support for precision agriculture and smart agriculture from concept to application, and collect crop production environmental information through wireless sensor networks to find problems in a timely and accurate manner, guide agricultural production, improve the quality and production efficiency of agricultural products, and transform the traditional agricultural production model based on manpower to the modern agricultural production model centered on information technology [18][19][20][21]. With the continuous emergence of new wireless communication technologies, for example, the LoRa technology in the low-power wide area network field is specifically designed for IoT applications. ...
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Based on the status quo of cultivated land, this paper analyzes the existing problems and builds a dynamic monitoring system for cultivated land protection. It works by using the Internet of Things technology and geographic and national conditions to realize the systematization, informatization, and socialization of cultivated land protection, thereby promoting the sustainable development of cultivated land and social stability and harmony. This paper puts forward relevant countermeasures and suggestions for the protection of cultivated land. This paper constructs the farmland protection dynamic monitoring system, proposes the goals of the system construction, points out the ideas of the system construction, and designs and analyzes the key points of the system composition. The system includes seven subsystems, and the functions and specific contents of the subsystems are explained, respectively, to build the entire system. Then, we put forward the financial, technical, and implementation problems of the system, and find out countermeasures, expand the system research, propose the development of the dynamic monitoring system of cultivated land protection in the direction of intelligence and convenience, and expand the application to food safety and disasters. In terms of forecasting, comprehensive evaluation of the existence and operation of the system is carried out by designing evaluation indicators and weights for the operation of the system.
... Among the IoT application domains, environmental monitoring is receiving increased attention as environmental technology becomes a key area of global sustainable development. For example, underwater resource management [3], wetland monitoring systems [4], emergency management communities [5], urban public safety emergency management early warning systems [6], and so on. These applications require the IoT to maintain a high availability for reliable execution. ...
Article
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Many environmental monitoring applications that are based on the Internet of Things (IoT) require robust and available systems. These systems must be able to tolerate the hardware or software failure of nodes and communication failure between nodes. However, node failure is inevitable due to environmental and human factors, and battery depletion in particular is a major contributor to node failure. The existing failure detection algorithms seldom consider the problem of node battery consumption. In order to rectify this, we propose a low-power failure detector (LP-FD) that can provide an acceptable failure detection service and can save on the battery consumption of nodes. From simulation experiments, results show that the LP-FD can provide better detection speed, accuracy, overhead and battery consumption than other failure detection algorithms.
... There are submerged hotels or water parks that offer attractions or panoramic views of marine fauna with facilities that need to be monitored [142,143], but most hotels have swimming pools, or spas are near beach or lake areas. There are also increasingly more proposals to extend IoT networks' functionalities to underwater systems, for which there are different communication alternatives based on acoustic, RF, or optical systems [144]. Radio waves suffer from a high attenuation in water [145] and, at low frequencies, require large antennas. ...
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In this paper, we explore the potential applications of Optical Wireless Communications in the tourism industry, considering both indoor and outdoor scenarios and different transmission speeds. They range from high-speed atmospheric outdoor links (Free-Space Optics (FSO)) to indoor systems based on high-speed lighting networks (known under the trade name LiFi©) or low-speed services support the Internet of Things networks, using visible light (VLC) or IR emitters, with receivers based on either on classical photodiodes or in image sensors, known as Optical Camera Communications. The avant-garde applications of this technology have been studied focusing on three possible use scenarios: the traveler himself, in what we have called TAN (Tourist Area Network); the tourist facility, which includes not only the hotel but also leisure areas (theme parks, museums, natural protected areas) or services (restaurants, shopping areas, etc.); and the entire destination, which can be both the city or the territory where the tourist is received, within the paradigm of the Smart Tourist Destination (STD). In addition to the classic services based on radio frequency and wired broadband networks, these technologies will make it possible to meet the tourist’s challenging needs, the establishment, and the destination. Besides, they cover the services imposed by the new marketing services related to location or context and feed the big data systems used to study tourist behavior.
... IoT (Internet of Things) is one of the important technologies that can be utilized [2], which is defined as "the infrastructure of the information society" . As we know, we first discussed the Internet of Underwater Things (IoUT) in 2012 [4]. ...
Article
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In the Internet of Things (IoT), the Internet of Underwater Things (IoUT) are smart underwater objects that can be interconnected. Environmental monitoring, underwater exploration, and disaster prevention are just a few practical applications that will be enabled by IoUT. It is recognized that IoUT is a promising technology for the development of smart cities because of its applications. Among the promising networking systems for supporting IoUT is the Underwater Wireless Sensor Network (UWSN). In contrast to traditional Territorial Wireless Sensor Networks (TWSN), UWSNs operate globally. IoUT will be faced with these unique properties. We explore IoUT in detail in this paper. The unique characteristics of underwater sensor networks (UWSNs), providing scalable and efficient routing services is very challenging. Due to the nature of radio signals in water, UWSNs use acoustic channels for communications. There are many orders of magnitude longer propagation delays in acoustic channels compared to radio-frequency channels. To address the challenging problem of routing in UWSNs, some routing protocols have been proposed. This protocol will increase the dynamic nature of routing in UWSN. This protocol subsequently displays a significant improvement in performance. The paper considers IoT applications for underwater environments using the carry-store-forwarding paradigm of Delay Tolerant Networking (DTN). The flooding of messages is one characteristic of routing protocols for DTN. As a result, the odds of delivery are increased, but on the other hand, each node has overhead in its buffer. Additionally, forwarding and receiving nodes have to spend a disproportionate amount of energy on this. By simulations, FBR protocol performance is evaluated for different angles and applications for Focused Beam Routing.
... IoUTs refer to internet-connected devices that can easily and legitimately retrieve information through cabled or wirelessenabled connectivity. UIoTs claims to be an extension and development phase of IoTs, which allows the extraction of anonymous information from smart ocean [317]. IoUTs are enabled by the most recent developments of AUVs, ROVs, smart underwater sensor networks, and routing protocols. ...
Article
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In recent years, underwater visible light communication (UVLC) has become a potential wireless carrier candidate for signal transmission in highly critical, unknown, and acrimonious water mediums such as oceans. Unfortunately, the oceans are the least explored reservoirs in oceanogeographical history. However, natural disasters have aroused significant interest in observing and monitoring oceanic environments for the last couple of decades. Therefore, UVLC has drawn attention as a reliable digital carrier and claims a futuristic optical media in the wireless communication domain. Counterparts of traditional communications, the green, clean, and safe UVLC support high capacity data-rate and bandwidth with minimal delay. Nevertheless, the deployment of UVLC is challenging rather than terrestrial basis communication over long ranges. In addition, UVLC systems have severe signal attenuation and strong turbulence channel conditions. Due to the fact that, this study provides an exhaustive and comprehensive survey of recent advancements in UVLC implementations to cope with the optical signal propagation issues. In this regard, a wide detailed summary and future perspectives of underwater optical signaling towards 5G and beyond (5GB) networks along with the current project schemes, channel impairments, various optical signal modulation techniques, underwater sensor network (UWSN) architectures with energy harvesting approaches, hybrid communication possibilities, and advancements of Internet of underwater things (IoUTs) are concluded in this research.
... Emerging UWSNs are expected to perform collaborative target monitoring in order to fully realize a smart connected network of subaquatic sensors with intelligent computing, massive data processing, self-learning and adaptive decision-making capabilities [4,5,23,26]. Due to these technological enhancements, IoUT solutions are practically considered as an indispensable ingredient and essential asset for realizing smart cities [6,7,36,47,51]. ...
Article
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This paper addresses poor cluster formation and frequent Cluster Head (CH) failure issues of underwater sensor networks by proposing an energy-efficient hierarchical topology-aware clustering routing (EEHTAC) protocol. In this paper, fault-tolerant backup clustering (FTBC) algorithms and multi-parameter cluster formation (MPCF) model were developed for the EEHTAC operation. The MPCF model tackles the issue of poor cluster formation performance by integrating multiple parameters to achieve effective clustering process. The FTBC algorithms tackle the issue of frequent CH failures to avoid interruption in data transmission. Performance of the MPCF model was evaluated using normal, high-fault, and high routing overhead network scenarios. Performance metrics employed for this analysis are temporal topology variation ratio (TTVR), CH load distribution (CLD), and cluster stability (STB). Obtained results show that operating with a CH retention period of 90s achieves better CH duty cycling per round and improves the MPCF process with values of 25.69%, 55.56%, and 60% for TTVR, CLD, and STB respectively. Performance of the FTBC-based EEHTAC was evaluated relative to Energy-balanced Unequal Layering Clustering (EULC) protocol. Performance indicators adopted for this evaluation are routing overhead (Ω), end to end delay (Δ), CH failures recovered (CFR), CH failures detected (CFD), received packets (θ), and energy consumption (Σ). With reference to the best obtained values, EEHTAC demonstrated performance improvement of 58.40%, 29.94%, 81.33%, 28.02%, 86.65%, and 54.35% over EULC variants in terms of Ω, Δ, CFR, CFD, θ, and Σ respectively. Obtained results displayed that the MPCF model is efficient for cluster formation performance and the FTBC-based EEHTAC protocol can perform effectively well against an existing CBR protocol.
... Emerging UWSNs are expected to perform collaborative target monitoring in order to fully realize a smart connected network of subaquatic sensors with intelligent computing, massive data processing, self-learning and adaptive decision-making capabilities [4,5,23,26]. Due to these technological enhancements, IoUT solutions are practically considered as an indispensable ingredient and essential asset for realizing smart cities [6,7,36,47,51]. ...
Preprint
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This paper addresses poor cluster formation and frequent Cluster Head (CH) failure issues of underwater sensor networks by proposing an energy-efficient hierarchical topology-aware clustering routing (EEHTAC) protocol. In this paper, fault-tolerant backup clustering (FTBC) algorithms and multi-parameter cluster formation (MPCF) model were developed for the EEHTAC operation. The MPCF model tackles the issue of poor cluster formation performance by integrating multiple parameters to achieve effective clustering process. The FTBC algorithms tackle the issue of frequent CH failures to avoid interruption in data transmission. Performance of the MPCF model was evaluated using normal, high-fault, and high routing overhead network scenarios. Performance metrics employed for this analysis are temporal topology variation ratio (TTVR), CH load distribution (CLD), and cluster stability (STB). Obtained results show that operating with a CH retention period of 90s achieves better CH duty cycling per round and improves the MPCF process with values of 25.69%, 55.56%, and 60% for TTVR, CLD, and STB respectively. Performance of the FTBC-based EEHTAC was evaluated relative to Energy-balanced Unequal Layering Clustering (EULC) protocol. Performance indicators adopted for this evaluation are routing overhead ({\Omega}), end to end delay ({\Delta}), CH failures recovered (CFR), CH failures detected (CFD), received packets ({\theta}), and energy consumption ({\Sigma}). With reference to the best obtained values, EEHTAC demonstrated performance improvement of 58.40%, 29.94%, 81.33%, 28.02%, 86.65%, and 54.35% over EULC variants in terms of {\Omega}, {\Delta}, CFR, CFD, {\theta}, and {\Sigma} respectively. Obtained results displayed that the MPCF model is efficient for cluster formation performance and the FTBC-based EEHTAC protocol can perform effectively well against an existing CBR protocol.
... This combination is intended to provide high-speed Internet access in the rural, urban, desert, and sea areas as shown in Fig 11. Such integration could play an essential role in enabling the emerging Internet of underwater things (IoUT) communications systems [356]. IoUT communication is essential for lowcost transportation, positioning and navigation, monitoring and security, and disaster prediction and prevention. ...
Article
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The commercial fifth-generation (5G) wireless communications networks have already been deployed with the aim of providing high data rates. However, the rapid growth in the number of smart devices and the emergence of the Internet of Everything (IoE) applications, which require an ultra-reliable and low-latency communication, will result in a substantial burden on the 5G wireless networks. As such, the data rate that could be supplied by 5G networks will unlikely sustain the enormous ongoing data traffic explosion. This has motivated research into continuing to advance the existing wireless networks toward the future generation of cellular systems, known as sixth generation (6G). Therefore, it is essential to provide a prospective vision of the 6G and the key enabling technologies for realizing future networks. To this end, this paper presents a comprehensive review/survey of the future evolution of 6G networks. Specifically, the objective of the paper is to provide a comprehensive review/survey about the key enabling technologies for 6G networks, which include a discussion about the main operation principles of each technology, envisioned potential applications, current state-of-the-art research, and the related technical challenges. Overall, this paper provides useful information for industries and academic researchers and discusses the potentials for opening up new research directions.
... Due to numerous implications in domains such as ecological, academic, industrial, and economic, the Internet of Underwater Things (IoUTs) has recently attracted the interest of many research and development activities in maritime industries [1][2][3][4]. The performance of IoUTs is influenced by optical and signals, primarily radio signals, which involve huge antennas and a lot of transmission energy because they move at low frequencies and across long distances. ...
Article
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The Internet of Underwater Things (IoUT) is an emerging area in marine science and engineering. It has witnessed significant research and development attention from both academia and industries due to its growing underwater use cases in oceanographic data collection, pollution monitoring, seismic monitoring, tactical surveillance, and assisted navigation for waterway transport. Information dissemination in the underwater network environment is very critical considering network dynamism, unattainable nodes, and limited resources of the tiny IoUT devices. Existing techniques are majorly based on location-centric beacon messages, which results in higher energy consumption, and wastage of computing resources in tiny IoUT devices. Towards this end, this paper presents an efficient void aware (EVA) framework for information dissemination in IoUT environment. Network architecture is modeled considering potential void region identification in the underwater network environment. An efficient void aware (EVA) information dissemination framework is proposed focusing on detecting void network region, and intelligent void aware data forwarding. The comparative performance evaluation attests to the benefits of the proposed framework in terms of energy consumption, network lifetime, packet delivery ratio, and end-to-end delay for information dissemination in IoUT.
... NDERWATER acoustic telemetry finds diverse applications in fields of subsea resource extraction such as resource exploration [1] , tracking the movements of aquatic and marine animals [2,3] , wireless communications for autonomous underwater vehicles (AUVs) [4] , and the emerging Internet of Underwater Things (IoUT) [5][6][7][8] . However, unlike terrestrial wireless communications systems, state-of-the-art acoustic telemetry systems suffer from limited data rates and energy efficiency, because of the characteristics of underwater communication, including bandwidth-limited underwater acoustic channels -generally recognized as the most challenging communication media in use today [9] -caused by high path loss [8] , time-varying multipath propagation [10] , large and variable propagation delay, node mobility caused by water currents [1] , and Doppler spread associated with the complex underwater environment [11] . ...
... But here we have considered free-floating sensors which are deployed several hundreds of meters underwater to collect data from a deep oceanic environment. 15 Transmission range depends on various parameters like pressure, temperature, and so forth. The transmission range of 1 to 8 km is indicated in different literatures. ...
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A well‐optimized and well‐performed communication network protocol is necessary to build successful underwater acoustic sensor networks (UWASNs). But for wired and wireless communication, medium access control (MAC) has a great effect on network performance and optimization. But unlike land‐based MAC protocols, underwater MAC protocols come with various challenges and issues like high propagation delay, limited bandwidth for communication signals, large attenuation in network signals, and the high noise level in signals. It is very challenging to build a well‐optimized underwater MAC protocol. Also, in UWASN, sensor nodes are generally divided into sub‐network parts to reduce the propagation delay of data signals. But this creates the problem of non‐uniform traffic load in sensor nodes. So, considering these issues, dynamic hold time MAC (DHT‐MAC) protocol is proposed here. In this protocol, depending on the distance from the central node, sensor nodes are divided into two sub‐network zones (parent node and child node). Depending on the traffic load and propagation delay, the child nodes can change their respective parent nodes dynamically. Advantage of the proposed method is that, if any of the parent nodes stops working, the child node will connect to the nearest parent node. When collecting the data signals, it has been observed that child nodes have a light traffic load compared to parent nodes. So dynamic cooperative transmission MAC (DCT‐MAC) protocol which is a contention‐based MAC protocol has been used in child nodes and as parent nodes have high traffic load, reservation‐based MAC protocol has been used.
... Despite these intrinsic difficulties, the vast diffusion of distributed systems in the most disparate contexts within the Internet of Things (IoT) framework has seen some researchers looking at the possible development of transmission channels in presence of water, even only for the realization of infrastructures shaped on limited requirements, as for example the transmission along the water surface or the data recovery from short underwater distances. The integration of these radio technologies with the more traditional acoustic and optical technologies presented in the previous section, has led to the definition of the so-called Internet of Underwater Things (IoUT) [18,19], thus translating the whole IoT infrastructural paradigm to the underwater environment. ...
Article
The aim of this paper is to demonstrate the exploitability of Long Range Wide Area Network (LoRaWAN) networking to set up a wireless transmission channel allowing the real time data collection from underwater depths up to more than 1 m. To this aim, a theoretical analysis is carried out to determine the actual feasibility of this link taking into account the technical features of the LoRa channel. Following this analysis, field tests in a swimming pool have been performed analyzing the transmission performance in terms of Received Signal Strength Indicator (RSSI) and Signal to Noise Ratio (SNR) for different transmission parameters and at increasing depths. Moreover, two test campaigns varying the antenna’s sensor node and the packet payload length have been performed Experimental results have seen a good corroboration of the theoretical analysis with efficient underwater LoRaWAN data transmission at depths up to 110 ±5 cm, considering 14 dBm transmitted power.
... Another critical factor for underwater MI communication is the eddy current loss due to the magnetic field. For instance, MI as a carrier in an aquatic environment can only achieve a range up to 30m at an operating frequency of 500 Hz [5]. ...
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div> Localization of sensor nodes in the Internet of Underwater Things (IoUT) is of considerable significance due to its various applications, such as navigation, data tagging, and detection of underwater objects. Therefore, in this paper, we propose a hybrid Bayesian multidimensional scaling (BMDS) based localization technique that can work on a fully hybrid IoUT network where the nodes can communicate using either optical, magnetic induction, and acoustic technologies. These communication technologies are already used for communication in the underwater environment; however, lacking localization solutions. Optical and magnetic induction communication achieves higher data rates for short communication. On the contrary, acoustic waves provide a low data rate for long-range underwater communication. The proposed method collectively uses optical, magnetic induction, and acoustic communication-based ranging to estimate the underwater sensor nodes’ final locations. Moreover, we also analyze the proposed scheme by deriving the hybrid Cramer-Rao lower bound (H-CRLB). Simulation results provide a complete comparative analysis of the proposed method with the literature. </div
... Also, artificial neural network and support vector machine quick simulation models were found to be useful in simulating dissolved, particulate and total heavy metal concentrations in aquatic environment based on physicochemical indices such as pH, suspended solids, temperature, total phosphorus and permanganate index [93] . These prediction models can be integrated with the existing resource constrained environment monitoring programmes and applied in a large-scale setting using the internet of underwater things which comes with different communication, monitoring and localization technologies [109] . Additionally, this may involve the progressive use of underwater micro-and nano-sensors; unmanned underwater vehicles; data transmission and storage tags; and information routing network protocols for active ecosystem surveillance. ...
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Aquaculture and fisheries sectors are finding ingenious ways to grow and meet the soaring human demand for nutrient-rich fish and seafood by efficiently utilizing the vast water resources and biodiversity of aquatic life on earth. This includes the progressive integration of information technology, data science and artificial intelligence with fishing and fish farming methods to enable intensification of aquaculture production, sustainable exploitation of natural fishery resources and mechanization-automation of allied activities. Exclusive data mining and machine learning systems are being developed to process complex datasets and perform intelligent tasks like analysing cause-effect associations, forecasting problems and providing smart-precision solutions for farming and catching fish. Considering the intensifying research and growing interest of stakeholders, in this review, we have consolidated basic information on the various practical applications of data mining and machine learning in aquaculture and fisheries domains from representative selection of scientific literature. This includes an overview of research and applications in 1) aquaculture activities such as monitoring and control of the production environment, optimization of feed use, fish biomass monitoring and disease prevention; 2) fisheries management aspects such as resource assessment, fishing, catch monitoring and regulation; 3) environment monitoring related to hydrology, primary production and aquatic pollution; 4) automation of fish processing and quality assurance systems; and 5) fish market intelligence, price forecasting and socioeconomics. While aquaculture has been relatively faster in integrating data mining and machine learning tools with advanced farming systems, capture fisheries is finding reliable methods to sort the complexities in data collection and processing. Finally, we have pointed out some of the challenges and future perspectives related to large-scale adoption.
... Sensor-web architectures (see del Río et al., 2017) are used to achieve process automation, sensor interoperation, and service synergy. Autonomy in the system is expanded relying on a range of unmanned platforms for surface-and underwater-operations (Domingo, 2012;Whitt et al., 2020). Cooperative and collaborative robotics approaches have been developed for autonomous marine vehicles, using different m2m communication and decision-making paradigms (Thompson and Guihen, 2019). ...
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The Internet of Underwater Things (IoUT) is the system of intelligent linked underwater things and a diverse kind of Internet of Things (IoT). IoUT is expected to permit different practicable requests, similar to ecological monitor, underwater examination, and calamity prohibition. With these uses, IoUT is considered unique of the likely technology around developed intelligent towns. To help the idea of IoUT, Underwater Wireless Sensor Networks (UWSNs) have appeared as an auspicious network system. UWSNs have various special characteristics, such a longer propagation delay, small bandwidth, and miserable reliability. This chapter presents challenges that can occur in IoUT. Also, the existing routing protocols for effective communication are discussed in great detail here. IoUT empowers a system of autonomous underwater vehicles (AUV) interconnecting with each other, detecting, collecting, and communicating data to sink node. Then, this data can be helpful in wide range of applications like ship wreckage detection, early discovery of tsunamis, marine health observing, as well as gathering real‐time oceanic info. This chapter focuses on the complete terminology of IoUT including its basic concept, architectural requirements, challenges, routing protocols, and machine learning algorithms in IoUT.
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The Internet of Underwater Things (IoUT) is the system of intelligent linked underwater things and a diverse kind of Internet of Things (IoT). IoUT is expected to permit different practicable requests, similar to ecological monitor, underwater examination, and calamity prohibition. With these uses, IoUT is considered as unique of the likely technology around developed intelligent towns. UWSN network system is favorable in the evolution of IoUT. In UWSN, many challenges exist that will be big challenge in evolution of IoUT. In this book chapter, basic concepts about the IoUT are presented like architecture, challenges, and application areas. UWSN and IoUT collectively help in many application areas like weather forecasting and monitoring. This chapter also presents introduction about new advance technology machine learning. How this helps in improving the application areas of underwater environment. Machine learning can also be used to explore minerals that exist below the water.
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With the improvements in machine-to-machine (M2M) communication, ubiquitous computing, and wireless sensor networks, the Internet of Things (IoT) has become a notion that is constantly rising in importance. Using uniquely addressable IDs, the Internet of Things links diverse physical items and allows them to communicate with one another through the Internet. A general overview of the IoT in the context of the architecture and associated technologies is provided in this article. On the other hand, the Internet of Things does not follow a standardised architecture model. This is accomplished by describing widely recognised architectural concepts that are subsequently refined with the associated technology in various tiers. Also included are some solutions that have been developed and future directions for addressing the obstacles faced by the IoT paradigm. Finally, the article discusses several Internet of Things applications to demonstrate the viability of the IoT idea in real-world settings.
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In this chapter, we study unmanned aerial vehicle (UAV) assisted mobile edge computing to optimize computing offloading with minimum UAV energy consumption. In the considered scenario, a UAV plays the role of an aerial server to collect and process the computing tasks offloaded by ground devices. Given the service requirements of devices, we jointly optimize the UAV trajectory, the device transmit power, and computing load allocation. The resulting optimization problem corresponds to nonconvex fractional programming, and the Dinkelbach algorithm and the successive convex approximation technique are adopted to solve it. Furthermore, we decompose the problem into multiple subproblems for distributed and parallel problem-solving. Simulation results demonstrate the effectiveness of the proposed approach for maximizing the energy efficiency of the UAV.
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Aquaculture is a sector that has seen unprecedented growth in recent years by acting as an alternative source for seafood production to fulfill global food demands and to compensate for the overexploitation of fishing. Various parameters such as environmental factors, production factors such as water quality, and biotic factors have to be monitored constantly to prevent losses in yield and increase efficiency. The Internet of Things (IoT) has transformed the aquaculture sector by providing real-time monitoring solutions remotely without much human intervention. Usually, the IoT technologies in aquaculture use a local server and store the huge amount of generated data in an Excel file or a database. This in turn exerts a lot of pressure on the Internet infrastructure. Cloud computing complements IoT by providing a virtual storage place and pathway for the vast amounts of data and programs to be stored and accessed. It not only increases the efficiency and scalability of the techniques but also allows a better collaboration between developers situated remotely. This chapter introduces the readers to the basic concepts of cloud computing and identifies the current area of its application in IoT. We will see how cloud computing can integrate with IoT technologies and offer more accountable solutions to various challenges. It also provides a discussion on future scope and trends for the same.
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There are many situations where it is important to accurately know the behavior of fish as a function of time and space in a fixed three dimensional volume. For example, optimal design of techniques that minimize mortality of fish approaching hydroelectric dams or approaching cooling intakes for a power plant require knowledge of the temporal and spatial behavior of fish near the structure of interest. The spatial and temporal behavior of fish in other fixed volumes such as estuaries and open rivers is also of interest for many migrating fish stocks. Both active acoustic (echo sounding) and systems that use acoustic emitting tags implanted in fish have been used to collect spatial and temporal fish behavior data. Active acoustic systems, including those with electronically and mechanically steered beams, can only acoustically ensonify a small part of the total volume of interest at any given time. Tag systems, on the other hand, can be used to monitor the behavior for the tagged fish over the entire volume of interest. A number of advances in the implementation, deployment and analysis of acoustic tag systems have been made over the past few years. Some of these improvements include techniques for optimally locating the receiving hydrophones to minimize the measured location errors, the development of acoustic signal waveforms that provide both unique target identification and accurate location estimates and the development of tracking algorithms that associate and track the multiple returns from an individual fish. These various techniques will be described. Guidelines for selecting the various parameters for the tag system including the positions of the hydrophones will be presented. Specific examples that compare the predicted and actual performance of the tag systems will be presented.
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