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An overview of the internet of underwater things
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.
... Monitoring and research tasks based on IoT technologies may be solved on both small and large scales (e.g., monitoring of vast water areas and parts of the sea). Examples of application models for monitoring tasks are given in [1][2][3][4]. Military security applications include protecting waters, port infrastructure and ships, mine clearance, communications with submarines and divers [3,5,6]. The mentioned application scenarios usually refer to the Internet of Underwater Things (IoUT) or Underwater Internet of Things (UIoT) technologies [1][2][3][4]7]. ...
... Examples of application models for monitoring tasks are given in [1][2][3][4]. Military security applications include protecting waters, port infrastructure and ships, mine clearance, communications with submarines and divers [3,5,6]. The mentioned application scenarios usually refer to the Internet of Underwater Things (IoUT) or Underwater Internet of Things (UIoT) technologies [1][2][3][4]7]. ...
... Military security applications include protecting waters, port infrastructure and ships, mine clearance, communications with submarines and divers [3,5,6]. The mentioned application scenarios usually refer to the Internet of Underwater Things (IoUT) or Underwater Internet of Things (UIoT) technologies [1][2][3][4]7]. ...
... It is of paramount significance to explore these oceanic areas. In this regard, the IoUT has emerged as a promising technology to support underwater discovery and exploration [1]. The IoUT is considered a remarkable revolution in communication and computing. ...
... Researchers are also focusing on IoT communication protocols for underwater drones. In [1], the author proposed a novel architecture for the IoUT and discussed its principle and key differences with the IoT. That study also addresses the applications of and challenges facing the IoUT. ...
... Data collection includes sensing, tracking, storing and streaming information. In [1], the authors proposed an IoUT system architecture based on perception, network, and application layers. Furthermore, Qiu et al. [34] proposed an IoUT architecture comprised of five layers, i.e., application, network, fusion, communication, and sensing layers. ...
Oceans cover more than 70% of the Earth's surface. For various reasons, almost 95% of these areas remain unexplored. Underwater wireless communication (UWC) has widespread applications , including real-time aquatic data collection, naval surveillance, natural disaster prevention, archaeological expeditions, oil and gas exploration, shipwreck exploration, maritime security, and the monitoring of aquatic species and water contamination. The promising concept of the Internet of Underwater Things (IoUT) is having a great influence in several areas, for example, in small research facilities and average-sized harbors, as well as in huge unexplored areas of ocean. The IoUT has emerged as an innovative technology with the potential to develop a smart ocean. The IoUT framework integrates different underwater communication techniques such as optical, magnetic induction, and acoustic signals. It is capable of revolutionizing industrial projects, scientific research, and business. The key enabler technology for the IoUT is the underwater wireless sensor network (UWSN); however, at present, this is characterized by limitations in reliability, long propagation delays, high energy consumption, a dynamic topology, and limited bandwidth. This study examines the literature to identify potential challenges and risks, as well as mitigating solutions, associated with the IoUT. Our findings reveal that the key contributing elements to the challenges facing the IoUT are underwater communications, energy storage, latency, mobility, a lack of standardization, transmission media, transmission range, and energy constraints. Furthermore, we discuss several IoUT applications while highlighting potential future research directions.
... Mounting a solar panel on floating objects such as buoys is one of the practical examples of exploiting solar energy for powering IoUT devices. However, in the case of solar-powered AUVs, these devices are pre-programmed to submerge and also to operate at the surface during the daytime for battery charging [44]. For a specific operating mode (such as diving, thrust, communication, and floating modes) during a given nth time slot, the harvested power of a solar-powered AUV can be given in (5) [45], as ...
... • Solar spectrum in water: The use of solar-based EH for deep water applications performs poorly due to the strong absorption of higher wavelengths of the sunlight spectrum with increasing water depth [128]. Though in the case of mobile underwater devices such as AUVs, they can be programmed to operate on the surface during the daytime for EH and submerge to continue their tasks when they are fully charged [44]. However, this approach may become ineffective due to the likelihood of missed events during the execution of a critical task. ...
... In recent years, the underwater internet of things (UIoT), which can obtain real-time ocean data and transmit it to the shore for further analysis and processing, is regarded as a new paradigm of ocean remote sensing. Figure 1 illustrates the basic schematic of the UIoT, encompassing various modules for underwater sensing and transmission (underwater sensor nodes and surface nodes), underwater computing and transmission [autonomous underwater vehicles (AUVs)], surface computing and transmission [surface base station (BS), surface ships, and surface nodes], as well as coastal control (seashore BS and seashore control center) [3][4][5]. ...
... In the HH-VBF protocol, the concept of the virtual routing pipe is adopted, where per hop virtual pipe for each forwarder is used, and each intermediate node makes decision about the pipe direction according to the current location. Hence, although the number of neighboring nodes is small, the HH-VBF protocol 3 can still find a data delivery path as long as a sensor node is available in the forwarding path within the communication range. However, the hop-by-hop nature introduces much more signaling overhead for the HH-VBF protocol. ...
Underwater acoustic sensor network (UASN) plays a crucial role in collecting real-time data from remote areas of the ocean. However, deploying the UASN is a challenging problem due to the harsh environment and high deployment cost. Therefore, it is essential to design an appropriate routing protocol to effectively address the issues of routing void, packet delivery delay, and energy utilization. In this paper, an adaptive support-vector-machine-based routing (ASVMR) protocol is proposed for the UASN to prolong the network lifetime and reduce the end-to-end packet delivery delay. The proposed protocol employs a distributed routing approach that dynamically optimizes the routing path in real-time by considering four types of node state information. Moreover, the ASVMR protocol establishes a "routing vector" spanning from the current node to the sink node, and selects a suitable pipe radius according to the packet delivery ratio (PDR). In addition, the ASVMR protocol incorporates future states of sensor nodes into the decision-making process, along with the adoption of a waiting time mechanism and routing void recovery mechanism. Extensive simulation results demonstrate that the proposed ASVMR protocol performs well, in terms of the PDR, the hop count, the end-to-end delay, and the energy efficiency in dynamic underwater environments.
... Nonetheless, the transmitted signals experience the underwater path, producing a notable attenuation. For this reason, estimating losses in such contexts is fundamental whenever an underwater measurement system has to be designed [98,99,100], where sensor nodes are deployed both underwater and abovewater. Therefore, network links may be labelled as Underwater-to-Underwater (UW2UW), Underwater-to-Abovewater (UW2AW), and Abovewater-to-Underwater (AW2UW). ...
... Since the fountain had a mix of rainwater and water coming from the city aqueduct, and owing to the fact that no salt was added, such water can be considered as salt free. 98 5. Underwater-to-Abovewater Links ...
Distributed measurement systems are spread in the most diverse application scenarios, and Internet of Things (IoT) transmission equipment is usually the enabling technologies for such measurement systems that need to feature wireless connectivity to ensure pervasiveness. Because wireless measurement systems have been deployed for the last years even in critical environments, assessing transmission technologies performances in such contexts is fundamental. Indeed, they are the most challenging ones for wireless data transmission due to their intrinsic attenuation capabilities. Several scenarios in which measurement systems can be deployed are analysed. Firstly, marine contexts are treated by considering above-the-sea wireless links. Such setting can be experienced in whichever application requiring remote monitoring of facilities and assets that are offshore installed. Some instances are offshore sea farming plants, or remote video monitoring systems installed on seamark buoys. Secondly, wireless communications taking place from the underground to the aboveground are covered. This scenario is typical of precision agriculture applications, where the accurate measurement of underground physical parameters is needed to be remotely sent to optimise crops reducing the wastefulness of fundamental resources (e.g., irrigation water). Thirdly, wireless communications occurring from the underwater to the abovewater are addressed. Such situation is inevitable for all those infrastructures monitoring conservation status of underwater species like algae, seaweeds and reef. Then, wireless links happening traversing metal surfaces and structures are tackled. Such context is commonly encountered in asset tracking and monitoring (e.g., containers), or in smart metering applications (e.g., utility meters). Lastly, sundry harsh environments that are typical of industrial monitoring (e.g., vibrating machineries, harsh temperature and humidity rooms, corrosive atmospheres) are tested to validate pervasive measurement infrastructures even in such contexts that are usually experienced in Industrial Internet of Things (IIoT) applications. The performances of wireless measurement systems in such scenarios are tested by sorting out ad-hoc measurement campaigns. Finally, IoT measurement infrastructures respectively deployed in above-the-sea and underground-to-aboveground settings are described to provide real applications in which such facilities can be effectively installed. Nonetheless, the aforementioned application scenarios are only some amid their sundry variety. Indeed, nowadays distributed pervasive measurement systems have to be thought in a broad way, resulting in countless instances: predictive maintenance, smart healthcare, smart cities, industrial monitoring, or smart agriculture, etc. This Thesis aims at showing distributed measurement systems in critical environments to set up pervasive monitoring infrastructures that are enabled by IoT transmission technologies. At first, they are presented, and then the harsh environments are introduced, along with the relative theoretical analysis modelling path loss in such conditions. It must be underlined that this Thesis aims neither at finding better path loss models with respect to the existing ones, nor at improving them. Indeed, path loss models are exploited as they are, in order to derive estimates of losses to understand the effectiveness of the deployed infrastructure. In fact, some transmission tests in those contexts are described, along with providing examples of these types of applications in the field, showing the measurement infrastructures and the relative critical environments serving as deployment sites. The scientific relevance of this Thesis is evident since, at the moment, the literature lacks a comparative study like this, showing both transmission performances in critical environments, and the deployment of real IoT distributed wireless measurement systems in such contexts.
... As in terrestrial environments, where smart sensors interact without human intervention, the same principle is applied in aquatic environments to determine the characteristics of the environment and monitor animals, people, plants, and objects in rivers and/or oceans, all using the paradigm known as the UIoT [5]. The implementation of the UIoT paradigm can be beneficial in the context of autonomous underwater vehicles (AUVs) for data management in which provide a user interface for managing and organizing this data [6] or in algorithms for data collection to improve data collection efficiency and overcome the limitations caused by node mobility [7]. ...
... where a i is the amplitude, k i = 2π/λ i is the wavenumber, and α i is the phase of the ith frequency component ( f i ). Likewise, the expected amplitude (µ i ) of each frequency component can be calculated as in [22]: where S η (ω i ) is the spectrum of ocean waves that can be obtained using (5), and ∆ω is the width of the frequency range of the spectrum (S η (ω)). At the location of the buoy, x = 0; therefore, ...
This paper is focused on the use of radio frequency identification (RFID) technology operating at 125 kHz in a communication layer for a network of mobile and static nodes in marine environments, with a specific focus on the Underwater Internet of Things (UIoT). The analysis is divided into two main sections: characterizing the penetration depth at different frequencies and evaluating the probabilities of data reception between antennas of static nodes and a terrestrial antenna considering the line of sight (LoS) between antennas. The results indicate that the use of RFID technology at 125 kHz allows for data reception with a penetration depth of 0.6116 dB/m, demonstrating its suitability for data communication in marine environments. In the second part of the analysis, we examine the probabilities of data reception between static-node antennas at different heights and a terrestrial antenna at a specific height. Wave samples recorded in Playa Sisal, Yucatan, Mexico, are used for this analysis. The findings show a maximum reception probability of 94.5% between static nodes with an antenna at a height of 0 m and a 100% data reception probability between a static node and the terrestrial antenna when the static-node antennas are optimally positioned at a height of 1 m above sea level. Overall, this paper provides valuable insights into the application of RFID technology in marine environments for the UIoT, considering the minimization of impacts on marine fauna. The results suggest that by adjusting the characteristics of the RFID system, the proposed architecture can be effectively implemented to expand the monitoring area, considering variables both underwater and on the surface of the marine environment.
... Furthermore, [12,15,23] ignore the high energy consumption ratio. In case of error estimation, [2,4,[6][7][8]10,11,[13][14][15][16][17][20][21][22][23]25] did not investigate their impact. However, [10][11][12][14][15][16]19,21,22,27] are good for maintaining energy and prolong the network lifetime. ...
... However, [10][11][12][14][15][16]19,21,22,27] are good for maintaining energy and prolong the network lifetime. Moreover, [2][3][4][5][6]10,[12][13][14][15][16][17]19,22,23] are proven to be delay-oriented techniques. It is interesting to note that none the localization techniques/algorithms were previously tested with BC. ...
Conventional underwater technologies were not able to provide authentication and proper visualization of unexplored ocean areas to accommodate a wide range of applications. The aforesaid technologies face several challenges including decentralization, beacon node localization (for identification of nodes), authentication of Internet of Underwater Things (IoUTs) objects and unreliable beacon node communication between purpose oriented IoT-enabled networks. Recently, new technologies such as blockchain (BC) and the IoUTs have been used to reduce the issues but there are still some research gaps; for example, unreliable beacon messages for node acquisition have significant impacts on node identification and localization and many constrained node resources, etc. Further, the uncertainty of acoustic communication and the environment itself become problems when designing a trust-based framework for the IoUTs. In this research, a trust-based hybrid BC-enabled beacon node localization (THBNL) framework is proposed to employ a secure strategy for beacon node localization (BNL) to mine the underwater localized nodes via the hybrid blockchain enabled beacon node localization (HB2NL) algorithm. This framework helps to merge two disciplines; it is hybrid because it follows the nature and bio inspired meta heuristics algorithms for scheduling the beacon nodes. The performance of the proposed approach is also evaluated for different factors such as node losses, packet delivery ratios, residual and energy consumption and waiting time analysis, etc. These findings show that the work done so far has been successful in achieving the required goals while remaining within the system parameters.
... Autonomous sensors with in-built automatic selfvalidating properties/capabilities have been proposed as a possible solution to save costs related to manual data quality control and at the same time increase the data quality and meet the challenges related to sensor coverage over vast subsea areas and over longer time [4], [5], [6], [7], [8]. Sensor selfchecking can be done with different methods and to different degrees. ...
The reliability of water quality measurement is crucial for sustainable use of ocean resources, climate and ecosystem models, and industrial applications. However, measurement stations in remote locations face limitations in terms of power, communication, and maintenance, posing challenges for data quality.
Even though some basic (near) real-time automatic tests are proposed in oceanographic measurement guidelines, time- and resource consuming Delayed Mode Quality Control is still required before using measurement data in forecasting, models, or decision-making.
To design effective quality control tests for more autonomous sensors with self-validating capabilities in real-time, a good understanding of expected environmental effects or errors on sensor signals is necessary.
This paper focuses on the effect of biofouling on the measurement of selected water quality parameters such as conductivity, oxygen, and turbidity. Biofouling remains a major issue despite research on biofouling protection and anti-biofouling sensor design. Biofouling growth on underwater sensors can increase measurement errors and uncertainty, result in shorter operation times, and require costly manual work related to retrieval, cleaning, and re-deployment. For some measurement technologies, biofouling can result in noise, while for others, it may cause systematic drift or delay signal exchange.
Here, we propose quality control tests designed to automatically detect and assess the impact of biofouling on sensor signals. These tests are applied to measurement data sets with a known presence of biofouling from Austevoll (Norway). We comment on the challenges of designing tests and setting adequate thresholds. We show that a detailed understanding of biofouling effect on sensors is crucial for designing effective near real-time quality control procedures.
Automatic, in-situ tests can save costs related to manual data quality control and increase data quality, thereby enabling well-informed decisions in ocean resource management, climate and ecosystem modeling, and industrial applications.
... There has been a great deal of interest in investigating, evaluating, and designing underwater wireless optical communication (UWOC) systems in the recent past. This is due to the fact that optical wireless communication systems can enable high transmission rates and reliable communication in oceanic channels over short distances [1]- [3]. Beam absorption, pointing errors, and underwater turbulence are the major impediments affecting UWOC systems. ...
In this paper, we have investigated the performance of an underwater vertical wireless optical communication (UVWOC) link employing multiple input-multiple output (MIMO) operating in conjunction with equal gain combing (EGC) techniques perturbed by weak and strong turbulence in the presence of pointing errors and attenuation losses. Vertical underwater turbulence, which varies from layer to layer due to temperature and salinity variation connected to depth, is modeled using hyperbolic tangent log-normal (HTLN) distribution in the case of weak underwater turbulence and gamma-gamma (GG) distribution in the case of strong underwater turbulence. Novel closed-form expressions quantifying the average bit error rate (BER) have been derived for the UVWOC MIMO EGC system for weak and strong turbulence regimes. The expression for the average BER associated with the UVWOC link for different values of pointing error, differing vertical layer depth, modulation types, and differing numbers of sources and detectors have been determined. In addition, closed-form expressions for the outage probability (OP) and ergodic channel capacity (ECC) have been derived for the UVWOC MIMO EGC system. The accuracy of all closed-form expressions derived in the paper has been verified using Monte Carlo simulations.
... Such platforms would enable the sharing of information and promote widespread engagement. A promising technological framework for enhancing conservation efforts is the Internet of Underwater Things (IoUT), a global network of interconnected underwater devices capable of sensing, interpreting, and reacting to their environment (Domingo, 2012;Cardia et al., 2019). The IoUT employs powerful tracking technologies and embedded sensors, all connected via the internet and smartphones, offering an innovative approach for the Blue Economy sector. ...
Attaining an equitable Blue Economy requires reconsidering historical extractive usages of natural ocean capital in favor of more sustainable activities. Scuba diving is an expanding industry, and several examples illustrate how the diving sector has assisted with transitions to sustainable economic activities. In certain countries diving tourism generates revenues comparable with fishing industries, yet the sector remains underrepresented within marine conservation efforts. Therefore, we present five actions tailored to enhance the diving sector’s participation in the Blue Economy: i) Organize the fragmented sector via international associations and federations; ii) Recognize usage rights for natural capital equal to extractive activities; iii) Modernize the sector using technology to improve connectivity and data sharing; iv) Invest in the sector by engaging private and public funding and subsidizing critical infrastructure to enable equitable access; v) Foster a sense of community by training and supporting local leaders, thereby ensuring more equitable participation by including women, indigenous people, and the youth. Diving represents one of the only endeavors that enables citizens to actively support the Blue Economy and help to achieve the United Nations Sustainable Development Goal 14, “Life Below Water”; therefore, the diving sector is uniquely poised to help address conservation goals and sustainable development.
... Since P2P CNN techniques are becoming more prevalent in Internet applications, integrating IoT into this context is another prospect to inspect [187]. Similarly, only a few studies have explored the use of IoT underwater and how to develop delay-tolerant IoT systems, both of which are attractive themes for continued investigations in the future [188,189]. ...
Given the exponential expansion of the internet, the possibilities of security attacks and cybercrimes have increased accordingly. However, poorly implemented security mechanisms in the Internet of Things (IoT) devices make them susceptible to cyberattacks, which can directly affect users. IoT forensics is thus needed for investigating and mitigating such attacks. While many works have examined IoT applications and challenges, only a few have focused on both the forensic and security issues in IoT. Therefore, this paper reviews forensic and security issues associated with IoT in different fields. Future prospects and challenges in IoT research and development are also highlighted. As demonstrated in the literature, most IoT devices are vulnerable to attacks due to a lack of standardized security measures. Unauthorized users could get access, compromise data, and even benefit from control of critical infrastructure. To fulfil the security-conscious needs of consumers, IoT can be used to develop a smart home system by designing a FLIP-based system that is highly scalable and adaptable. Utilizing a blockchain-based authentication mechanism with a multi-chain structure can provide additional security protection between different trust domains. Deep learning can be utilized to develop a network forensics framework with a high-performing system for detecting and tracking cyberattack incidents. Moreover, researchers should consider limiting the amount of data created and delivered when using big data to develop IoT-based smart systems. The findings of this review will stimulate academics to seek potential solutions for the identified issues, thereby advancing the IoT field.
... In recent years, the underwater internet of things (UIoT), which can obtain real-time oceanic data and transmit it to the shore for further analysis and processing, is regarded as a new paradigm of ocean remote sensing. Figure 1 illustrates the basic schematic of the UIoT, encompassing various modules for underwater sensing and transmission (underwater sensor nodes and surface nodes); underwater computing and transmission (autonomous underwater vehicles (AUVs)); and surface computing and transmission (surface base station (BS), surface ships, and surface nodes), as well as coastal control (seashore BS and seashore control center) [3][4][5]. Deploying the UASN poses challenges due to the demanding environmental conditions and substantial deployment costs. First, the sound signal propagates much more slowly in the water, at approximately 1500 m/s, leading to noticeable latency in signal propagation. ...
The underwater acoustic sensor network (UASN) plays a crucial role in collecting real-time data from remote areas of the ocean. However, the deployment of UASN poses significant challenges due to the demanding environmental conditions and the considerable expenses associated with its implementation. Therefore, it is essential to design an appropriate routing protocol to effectively address the issues of packet delivery delay, routing void, and energy consumption. In this paper, an adaptive support vector machine (SVM)-based routing (ASVMR) protocol is proposed for the UASN to minimize end-to-end delay and prolong the network lifetime. The proposed protocol employs a distributed routing approach that dynamically optimizes the routing path in real time by considering four types of node state information. Moreover, the ASVMR protocol establishes a “routing vector” spanning from the current node to the sink node and selects a suitable pipe radius according to the packet delivery ratio (PDR). In addition, the ASVMR protocol incorporates future states of sensor nodes into the decision-making process, along with the adoption of a waiting time mechanism and routing void recovery mechanism. Extensive simulation results demonstrate that the proposed ASVMR protocol performs well in terms of the PDR, the hop count, the end-to-end delay, and the energy efficiency in dynamic underwater environments.
... Autonomous underwater vehicles (AUVs), remotely operated underwater vehicles (ROUVs), and remote sensors and communication networks are commonly used for intelligence, surveillance and reconnaissance missions, for monitoring underwater conditions and resources, and for surveying unexplored regions of our oceans [1][2][3] . An extensive, continuously operated network of these devices, that is, an Internet of Underwater Things (IoUT) (Fig. 1a) 4,5 , would grant unparalleled opportunity for the large-scale implementation of such activities. However, the deployment of such a network is currently prohibited by the relatively short power cycles of batteries and the lack of persistent onboard power sources. ...
... The majority of the proposed WuRxs are RF-based, and designed for terrestrial wireless sensor networks [71]. Recently, acoustic solutions started to gain attention because of the significant advancements in the fields of underwater wireless sensor networks and acoustics [72]- [75]. Therefore, in this work, it has been decided to focus on the development of novel wake-up receivers architectures with State-of-the-Art performance for UAWSNs. ...
Wireless sensor networks (WSNs), due to their multidisciplinary applications, represent one of the main enabling technologies of the Internet-of-Things paradigm. These networks, consisting of sensor nodes characterized by processing and transmitting capabilities, are implemented in various fields such as oceanography, disaster prevention, the oil and gas industry, health, commercial, and military applications. A critical challenge in designing WSNs is optimizing the sensor node’s power consumption, which determines the network lifetime. One of the most efficient energy-saving approaches consists of integrating Wake-Up Receivers (WuRxs), which allow selective activation of the sensor nodes on demand. This thesis reports three novel WuRx architectures and six low power circuit implementations. Two of the implementations, one based on tunable current starved inverters and one on tunable NOR-based multivibrators, present the lowest power consumption reported for an underwater acoustic WuRx. Their performances have been experimentally validated through an ASIC (AMS-350nm CMOS process) by decoding an acoustic wake-up call transmitted underwater. Both circuits consume less than 500 nW. The tunable current starved inverter-based WuRx consumes 265 nW, it has an area of 0.058 mm^2, and a data rate of 250 bit/s. At simulation level, one of the circuit implementations (Single Transistor) presents the lowest power consumption reported for an acoustic WuRx (7.2 nW). In this thesis, also analytical models for the subthreshold operation of some Schmitt triggers (STs), which are extensively implemented in sensor node architectures, have been derived. The hysteresis voltages of a tunable ST and of a low power ST have been analytically modeled. The derived expressions provide physical insight into the behavior of the circuits, by relating the hysteresis voltages to the transistors’ geometrical parameters. Furthermore, the models can be used to predict the effect of supply voltage and temperature variations on the characteristics and to estimate the minimum supply voltage for which hysteresis occurs. The models have been experimentally validated, with a maximum error below 10 %, relative to the supply voltage. Overall, the proposed circuits and architectures can be used in implementation of low power sensor nodes.
... parts of a larger system can enable self-* to be realised. The Internet of Underwater Things (IoUT) is one example [32] that requires high autonomy because maintenance is expensive in the underwater ecosystem, and it is challenging to provide continuous human administration. Such systems must implement self-* capabilities to cater to the deployment in such extreme conditions. ...
With the rise of the Internet of Things (IoT), tiny devices capable of computation and data transmission are being deployed across various technological domains. Due to the wide deployment of these devices, manual setup and management are infeasible and inefficient. To address this inefficiency, intelligent procedures must be established to enable autonomy that allows devices and networks to operate efficiently with minimal human intervention. In the traditional client-server paradigm, autonomic computing has been proven effective in minimising user intervention in computer systems management and will benefit IoT networks. However, IoT networks tend to be heterogeneous, distributed and resource-constrained, mandating the need for new approaches to implement autonomic principles compared to traditional approaches. We begin by introducing the basic principles of autonomic computing and its significance in IoT. We then discuss the self-* paradigm and MAPE loop from an IoT perspective, followed by recent works in IoT and key enabling technologies for enabling autonomic properties in IoT. Based on the self-* paradigm and MAPE loop analysis from the existing literature, we propose a set of qualitative characteristics for evaluating the autonomy of the IoT network. Lastly, we provide a comprehensive list of challenges associated with achieving autonomic IoT and directions for future research.
... The high mobility profiles associated to these flying entities is likely to pose fidelity challenges given their continuous interfacing with other aerial and ground stations [67], [68]. In an effort to integrate oceanic vehicles or under sea components to existing communication networks, extensions of IoT to Underwater Internet of Things (UIoT) [69], [70] adds complexity to the overall topology formations in 6G. Building seamless connectivity between sensor nodes, unmanned Underwater Vehicle (UUV) etc., with mainstream infrastructure [71] through acoustic or optical channels reveals more privacy concerns that could emerge within the multi-layered setups [72]. ...
Communication infrastructures, i.e. machine-to-machine communication networks dedicated to provide certain means for participants to exchange information, become constantly more flexible and operate more dynamically. The evolution of underlying technologies introduces new features by which gradually new mechanisms and freedom in operation are enabled. Services can be dynamically redeployed during runtime, states be migrated between devices. Software-defined message exchange frameworks make data omni-available and establish interaction across all layers of abstraction. We analyze in this work various descriptive use cases for future mobile communications regarding the specific trust relations between different actors and point out the necessity for explicit trust management in the network.
... Clearly, a key development in channel modelling is the exact characterization of the amount of loss incurred by channel impulse response in UWOC systems. These new technology have made the UWC field has had remarkable growth in business, defense, and research which results further development in Internet of Underwater Things (IoUT) [12] & [15]. However, just one form of communication is incapable of satisfying the demands laid forward by the IoUT, because it involves a variety of applications and networks performance standards. ...
Underwater wireless optical communication (UWOC) technology was adopted recently to address the underwater communications' need for fast throughput and huge data transmission. In this system, Multiple Input Multiple Output (MIMO) transmission with the Generalized Frequency Division Multiplexing (GFDM) is implemented in UWOC System. Recently, the next-generation technology is made possible by using GFDM in MIMO systems. It combines the advantages of faster data rates with little out-of-band (OOB) emission and strong incoherent demodulation capacity. By employing Forward Error Correction (FEC) codes for channel encoding and decoding, including BCH and RS codes, to enhance system performance. Also, in order to provide efficient channel estimation, various equalizer methods such as Minimum Mean Square Error (MMSE), Zero Forcing (ZF) and NLMS decision feedback equalizers has been adopted at receiver side. Since the UWOC channel is mostly affected by turbulence, the channel’s temporal and geographical dispersion under various conditions have been investigated. In this work, Channel impulse response is obtained via Monte Carlo (MC) simulation while accounting for the absorption and scattering effects. The simulation results shows that BER performance of NLMS equalizer technique attain better performance in different code rates and the RS coding achieved the best BER of ~10-5 at less than 20dB itself. The pointing errors in UOC may occur due to uncertainties and environmental disturbances which could not be accurately assessed and controlled by optical alignment techniques. Hence, the BER performance of BCH coded and RS coded GFDM method with different pointing error have been analyzed and spatial diversity significantly reduces fading impairments. Additionally, the effect of turbulence is evaluated under various turbulence conditions.
... Clearly, a key development in channel modelling is the exact characterization of the amount of loss incurred by channel impulse response in UWOC systems. These new technology have made the UWC field has had remarkable growth in business, defense, and research which results further development in Internet of Underwater Things (IoUT) [12] & [15]. However, just one form of communication is incapable of satisfying the demands laid forward by the IoUT, because it involves a variety of applications and networks performance standards. ...
Underwater wireless optical communication (UWOC) technology was adopted recently to address the underwater communications' need for fast throughput and huge data transmission. In this system, Multiple Input Multiple Output (MIMO) transmission with the Generalized Frequency Division Multiplexing (GFDM) is implemented in UWOC System. Recently, the next-generation technology is made possible by using GFDM in MIMO systems. It combines the advantages of faster data rates with little out-of-band (OOB) emission and strong incoherent demodulation capacity. By employing Forward Error Correction (FEC) codes for channel encoding and decoding, including BCH and RS codes, to enhance system performance. Also, in order to provide efficient channel estimation, various equalizer methods such as Minimum Mean Square Error (MMSE), Zero Forcing (ZF) and NLMS decision feedback equalizers has been adopted at receiver side. Since the UWOC channel is mostly affected by turbulence, the channel’s temporal and geographical dispersion under various conditions have been investigated. In this work, Channel impulse response is obtained via Monte Carlo (MC) simulation while accounting for the absorption and scattering effects. The simulation results shows that BER performance of NLMS equalizer technique attain better performance in different code rates and the RS coding achieved the best BER of ~10-5 at less than 20dB itself. The pointing errors in UOC may occur due to uncertainties and environmental disturbances which could not be accurately assessed and controlled by optical alignment techniques. Hence, the BER performance of BCH coded and RS coded GFDM method with different pointing error have been analyzed and spatial diversity significantly reduces fading impairments. Additionally, the effect of turbulence is evaluated under various turbulence conditions.
... With the increasing requirements in a broad range of applications such as underwater environment monitoring and protection, disaster early warning, homeland defense, underwater vehicle navigation and underwater entertainment activities [1][2][3][4], the concept of the Internet of Underwater Things (IoUT) has continued to gain in popularity since the 2010s [5]. It is a global network of smart, interconnected underwater devices that enable unprecedented monitoring and surveillance of vast areas of our oceans and seas. ...
The most significant increase of current task is in the desire for operational flexibility and agility in large-scale underwater network application scenarios in recent years. In order to address the challenging problems in Underwater Wireless Sensor Networks (UWSNs), we propose a large-scale UWSN based on the cellular network architecture called Underwater Cellular (uw-Cellular) network. It is designed especially for application scenarios where a large number of both fixed and mobile network nodes exist in a wide area to monitor the underwater environment. We also design protocols in each network layer in order to ensure reasonable channel sharing, data forwarding path selection and data reliability. The purpose of the simulation study we implement is to evaluate the performance of the CLA routing strategy compared to the VBF and the MFLOOD protocols in the uw-Cellular network. We also deploy a twenty-node uw-Cellular network in the real-world environment as the field case study. The experimental results showed that the Data Rate between any nodes could reach above 500 bps, and the network Average Throughput was no less than 550 bps under various load situations.
... At the same time, a new type of smart city has aroused widespread attention, and researchers have accordingly proposed marine smart cities, e.g., the oceanix city [1], smart coastal city [2], and underwater smart cities [3]. The IoUT is defined as a worldwide network of interconnected underwater objects [4], considered as one of the potential inventions for creating smart city communities [5], and has become one of the current research hotspots in the marine field. ...
With the booming development of marine exploration technology, new studies such as the oceanix city, smart coastal city, and underwater smart cities have been proposed, and the Internet of Underwater Things (IoUT) has received a lot of attention. Data collection is an important application of the IoUT. The common method is to collect data by traversing the network using underwater intelligent devices, such as Autonomous Underwater Vehicles (AUVs). However, traditional data collection methods focus more on issues, such as path planning or the task assignment of AUVs. It is commonly known that the MAC protocol plays a crucial role in data transmission, which is designed to solve the competition issue for shared channels. However, the research on MAC is very challenging owing to the characteristics of hydroacoustic communication, e.g., the low bandwidth, high error rate, and long transmission latency. Hence, this paper proposes a MAC protocol based on an Interference Cancellation Graph (ICG-MAC) for AUV-assisted IoUT. It ensures that AUVs can join the network for data transmission immediately after arriving at the target area and they do not interfere with the normal work of other sensor nodes. Firstly, the target area to be reached by an AUV for data collection is defined according to the node degree and residual energy; then the interference model between neighboring nodes is analyzed and an Interference Cancellation Graphx is established, based on which the time slots are allocated for sensor nodes; and finally, the AUV moves to the target area for conflict-free data collection. The simulation results show that the proposed algorithm outperforms the comparison algorithms in terms of the network throughput and energy consumption. With the assistance of an AUV, better network connectivity and higher network traffic can be obtained.
... Wireless underwater sensor networks (WUSNs) provide round-the-clock data collection at higher spatial and temporal resolutions than is possible via any other means of underwater data collection. They are the foundation of the internet-ofunderwater-things (IoUTs), whereby sensors and underwater objects are networked to cover as much of the oceans as possible [1]. They provide vast amounts of data for training ML models for environmental and climate change research, industrial applications, and proactive early disaster prevention/early warning systems. ...
Life on earth depends on healthy oceans, which supply a large percentage of the planet's oxygen, food, and energy. However, the oceans are under threat from climate change, which is devastating the marine ecosystem and the economic and social systems that depend on it. The Internet-of-underwater-things (IoUTs), a global interconnection of underwater objects, enables round-the-clock monitoring of the oceans. It provides high-resolution data for training machine learning (ML) algorithms for rapidly evaluating potential climate change solutions and speeding up decision-making. The sensors in conventional IoUTs are battery-powered, which limits their lifetime, and constitutes environmental hazards when they die. In this paper, we propose a sustainable scheme to improve the throughput and lifetime of underwater networks, enabling them to potentially operate indefinitely. The scheme is based on simultaneous wireless information and power transfer (SWIPT) from an autonomous underwater vehicle (AUV) used for data collection. We model the problem of jointly maximising throughput and harvested power as a Markov Decision Process (MDP), and develop a model-free reinforcement learning (RL) algorithm as a solution. The model's reward function incentivises the AUV to find optimal trajectories that maximise throughput and power transfer to the underwater nodes while minimising energy consumption. To the best of our knowledge, this is the first attempt at using RL to ensure sustainable underwater networks via SWIPT. The scheme is implemented in an open 3D RL environment specifically developed in MATLAB for this study. The performance results show up 207% improvement in energy efficiency compared to those of a random trajectory scheme used as a baseline model.
... However, it is only applicable to smallscale networks and is affected by the range of sensor networks, which complicates its application in the marine environment alone [23]. In a complex marine environment, the interaction of network information is affected by large transmission noise, long transmission distance and less offshore energy, which results in a high rate of data packet loss and a delay in transmission, which poses an enormous threat to data security [24,25]. To solve these communication problems, technologies, such as a low-power wide-area network (LPWAN) and long-range radio (LoRa), are emerging, which not only enable efficient data transmission over long distances in harsh sea conditions, but also help the underwater Internet of Things (UIoT) to transmit underwater data, images and video, which provide a reference for the large-scale transmission of ocean data. ...
Marine aquaculture has become an important strategy to enable the ecological and sustainable development of fishery due to the decreasing natural fishery resources. To solve farming pain points, improve farming efficiency and modernize fisheries, new digital technologies, such as the Internet of Things, big data, cloud computing, artificial intelligence and blockchain, are increasingly being widely applied in aquaculture. This paper introduces the interrelationship of new digital technologies and the framework of their application in marine aquaculture. The results of the application of each new digital technology in marine aquaculture are highlighted, and the advantages or problems of each new digital technology in marine aquaculture are pointed out. Further, the application of new digital technologies in deep-sea aquaculture facilities is enumerated. Finally, the main problems faced by new digital technologies in the process of marine aquaculture production and the future development trend are sorted out and summarized to provide scientific reference for promoting the wide application of new digital technology in marine aquaculture.
... With the expansion of Internet-of-Things (IoT) technology, the ocean will be explored deeply by humans. Ocean buoys, satellites, aircraft, vessels, and vehicles have formed the satellite-terrestrial network, which will cover the ocean using the UWOC network in the near future [12]. Despite UWOC having significant achievements, the complexity of the underwater environment still raises challenges for UWOC. ...
With the development of underwater exploration, underwater networking is in urgent demand. At present, underwater wireless optical communication (UWOC) is primarily based on line-of-sight (LOS) communication links. However, the underwater environment is so complicated that LOS communication links are easily affected by a couple of factors such as air bubbles, turbidity, oceanic turbulence, and so on. We put forward novel UWOC links using the total reflection at the air-water interface, which can mitigate those phenomena. This paper aims to investigate a UWOC link based on the total reflection at the air-water interface. In our work, we achieved the maximum data rate of 300 Mb/s and a bit error rate (BER) of 3.10 × 10−3 under the forward error correction (FEC) with the total reflection angle of 7°. Furthermore, we verified the performance of the total reflection-based UWOC links at the air-water interface in the presence of waves and evaluated the impact on the UWOC links when the frequency and amplitude of the waves varied.
... Overview: Underwater Internet of Things (UW IoT) [2] is a novel class of IoTs [3]- [5], enabling various practical applications in aqueous environments such as oceanographic data collection, pollution and environmental monitoring, tsunami detection/disaster prevention, assisted navigation, and tactical surveillance [6], [7]. A new design has to be envisioned for sensors/things in UW IoT as traditional digital sensors are (i) expensive (cannot be deployed in high density); (ii) highpower consuming (need to be put to sleep, thus losing temporal granularity), and (iii) finally pollute the environment. ...
Reliable and persistent water monitoring is a challenging problem in smart Underwater Internet of Things (UW IoT) due to its harsh, unexplored, and unpredictable nature. Given the need for high-resolution spatio-temporal sensing in such environments, traditional digital sensors are not suitable due to their high cost, high power consumption, and non-biodegradable nature. Further, reliable and low latency communication techniques that avoid data packet retransmissions, if the feedback is available, are crucial for reconstructing the phenomenon being monitored in a timely manner at the fusion center, such as a drone. To address the above challenges, we propose a novel architecture consisting of a substrate of densely deployed underwater all-analog biodegradable sensors that enable persistent sensing and continually transmitting data to the surface digital buoys. The analog nodes are designed to be energy efficient by implementing analog Joint Source-Channel Coding (JSCC), a low-complexity compression-communication technique, using biodegradable Field Effect Transistors (FETs). We then propose a correlation-aware Hybrid Automatic Repeat Request (HARQ) technique to transmit data from the surface buoys to the fusion center. Such HARQ technique leverages JSCC and the redundancy in the buoy data (arising from the correlation of the phenomenon at the analog nodes) to avoid retransmissions, thus saving energy and time.
... The Internet-of-Underwater-Things (IoUT) is gaining increased interest as a promising concept that aims to bring ubiquitous connectivity to the underwater environment. The overarching goal of the research in this area is to connect underwater sensor networks (USNs) and autonomous underwater vehicles (AUVs) through reliable wireless links in order to facilitate seamless underwater operations such as undersea monitoring, marine life protection, oil and gas exploration, and navigation support, to name a few [1,2]. Communication in IoUT can be established based on three different types of propagation media, namely: acoustic, radio frequency (RF), and optical. ...
Intelligent reflecting surfaces (IRSs) offer paradigm shift towards enhancing the capabilities of wireless communications. The use of this emerging technology in the realm of underwater wireless systems is a promising solution to overcome the limitations pertinent to such challenging environments. In this paper, we quantify the performance enhancement offered by the integration of IRS technology in the context of underwater optical wireless communication (OWC). Specifically, we derive a closed-form expression for the outage probability over log-normal channels, taking into consideration the underwater attenuation, pointing error, and turbulence effects. The underwater turbulent medium is characterized by the recently introduced Oceanic Turbulence Optical Power Spectrum (OTOPS) model that uses the practical values of average temperature and salinity concentration in earth basins. The presented numerical results take into account the effects of the turbulent medium as well as the communication system parameters (i.e., communication range, receiver aperture diameter, number of IRS). Our results show that IRSs can offer significant enhancement in the reliability of underwater OWC systems under attenuation, beam displacement, and turbulence effects. Moreover, the combined effect of using a large number of reflecting surfaces and a larger aperture diameter yields a more noticeable improvement.
... Network planning includes conventional UWSNs planned from [3] and instantaneous UWSN planning in the shape of Internet of Underwater Things projected from [4]. UWSNs include nodules that are employable on the exterior and under water. ...
UWSNs (underwater wireless sensor networks) are essential for doing any type of task underwater. Huge broadcast lag, great error degree, small bandwidth, and restricted energy in Underwater Sensor Networks interest concentration of utmost investigators. In UWSNs, the efficient use of energy is one of the main problems, as the substitution of energy sources in this kind of location is extremely costly. UWSNs are utilized in many fields, like measuring pollution, issuing tsunami cautions, conducting offshore surveys, and strategic tracing. For numerous functions, the efficacy and dependability of network regarding prominent operation, energy preservation, small bit error rate, and decreased interruption are fundamental. Nevertheless, UWSN’s exclusive features like small bandwidth accessibility, large interruptions in broadcast, very vivacious network topology, and extreme possibility of error present numerous problems in the growth of effective and dependable communication procedures. As opposed to current deepness-based routing techniques, we are focusing on CoDBR (Cooperative Depth-based Routing) and CEEDBR (Cooperative Energy Efficient Depth-based Routing) procedures to improve network lifespan, energy efficacy, and amount.
... The past few decades have seen a growing demand for underwater acoustic sensor networks. With an ever-increasing range of applications, from offshore site monitoring to natural disaster alert systems and naval traffic surveillance, it has not come as a surprise that the vision of the Internet of Underwater Things has been proclaimed by researchers in the field [5]. There exist many standards in terrestrial wireless radio communication. ...
... IoUT has certain similarities to IoT such as its structure, function, and its energy limitation. However, a few differences exist, which are related mainly to the heterogeneity of assets in terms of their: (a) communication technologies, (b) tracking technologies, (c) low battery capacity and difficulty of recharge, (d) energy harvesting technologies, (e) network density, (f) localization techniques [17]. Therefore, as mentioned in [18], in order to successfully establish a UWCN/UWSN, and obtain IoUT capabilities, at least the following issues must be considered: (a) the communication medium, i.e., the water, (b) the dynamic changes of network topology, (c) the energy consumption and maintenance constraints, (d) the hazardous environment and physical security, and (e) localization [18]. ...
As maritime and military missions become more and more complex and multifactorial over the years, there has been a high interest in the research and development of (autonomous) unmanned underwater vehicles (UUVs). Latest efforts concern the modeling and simulation of UUVs’ collaboration in swarm formations, towards obtaining deeper insights related to the critical issues of cybersecurity and interoperability. The research topics, which are constantly emerging in this domain, are closely related to the communication, interoperability, and secure operation of UUVs, as well as to the volume, velocity, variety, and veracity of data transmitted in low bit-rate due to the medium, i.e., the water. This paper reports on specific research topics in the domain of UUVs, emphasizing interoperability and cybersecurity in swarms of UUVs in a military/search-and-rescue setting. The goal of this work is two-fold: a) to review existing methods and tools of semantic modeling and simulation for cybersecurity and interoperability on the Internet of Underwater Things (IoUT), b) to highlight open issues and challenges, towards developing a novel simulation approach to effectively support critical and life-saving decision-making of commanders of military and search-and-rescue operations.
This study was conducted for investigating the impact of irrigation interval and deficit irrigation on seed cotton yield, fiber quality, and water productivity of cotton (Gossypium hirsutum L.) in the Şanlıurfa province of Türkiye during the years 2020 and 2021. The experiment was conducted using a randomized complete block design with split plots. The main plots included three irrigation intervals (D1: 4 day, D2: 8 day, and D3: 12 day), while the sub-plots consisted of three irrigation levels (I1: %150, I2: %120, and I3: %90) considered by Class A pan evaporation using the drip irrigation method. The study resulted in that the crop evapotranspiration varied from 693 to 1153 mm in 2020 and from 716 to 1126 mm in 2021, respectively. Irrigation interval and deficit irrigation had a statistically significant effect on seed cotton yield, seed cotton weight, and ginning outturn in both years of the study. The highest seed cotton yield, seed cotton weight, and lint yield were obtained from the treatment with a 4-day irrigation interval and irrigation water level at 150% (D1-I1), while the lowest values were obtained from the treatment with a 12-day irrigation interval and irrigation water level at 90% (D3-I3). However, irrigation interval and deficit irrigation did not have a statistically significant effect on 100-seed weight, fiber fineness, fiber length, and fiber strength in both years of the study. In the study, water use productivity (WP) ranged from 0.32 to 0.55 kg m-3, while irrigation water use productivity (IWP) ranged from 0.33 to 0.59 kg m-3, and similar results were obtained in both years of the research. According to the research findings, to achieve the highest cotton yield and quality, an irrigation interval of 4 days and a total seasonal irrigation water of 1062 mm are recommended.
The ocean is vital for humankind but may cause catastrophes when unhealthy. Although there have been efforts to build ocean monitoring systems, the understanding of the underwater environment is limited due to the cost and challenges of obtaining real-time marine data. One potential solution is to build stationary ocean observation systems based on wireless communication due to its affordable cost. In this study, we divide these systems into three components: underwater data acquisition, network communication, and data management. We investigate the engineering challenges associated with each component, the causes, and how they relate. The literature has not discussed the technical issues of building stationary smart ocean monitoring systems entirely based on wireless communication yet. This paper fills that research gap by conducting semi-structured interviews with 17 experts knowledgeable about underwater sensors, underwater acoustic communication, offshore network communication, and underwater data usage. The identified challenges are compared with the literature to assess whether our findings are novel or are a confirmation of what have been already found in prior publications. The Internet of Things (IoT) used in smart city platforms is quite advanced, but the Internet of Underwater Things (IoUT) employed in smart ocean monitoring systems has several unresolved issues; although IoT is viewed as a foundation for IoUT. Therefore, we compare fundamental differences between the technologies used in the smart city and the smart ocean domains, explaining why some of our identified challenges are unique in the marine context.
Wireless information routing beneath the ocean, or usually underwater, has supplied the most excellent technical methods of oceanic observations. Traditionally, ocean bottoms have been monitored by placing oceanographic sensors that collect data at specific and defined ocean zones. When the duties are performed, the oceanographic instruments are recovered. Because there is no collaborative exchange of collected data between the collecting point and the monitoring end, data cannot be observed remotely. Underwater sensor networks can be wirelessly connected with sensors and monitors without extensive cable. Underwater wireless sensor networks are what they are called (UWSNs). This article investigates the various aspects of UWSNs, such as their significance, applications, network design, demands, routing, deployments and challenges.
Unmanned aerial vehicles (UAVs) have been widely devoted to mobile edge computing (MEC) systems that have limited resources to provide high-quality computing and communication services for Internet of Things (IoT) terminals. Energy-efficient computation and resource allocation are key issues for the sustainable operation of the above-mentioned systems. The 3D deployment optimization of multi-UAVs is also crucial to maximizing the system's computation efficiency. In this paper, we discuss a multi-UAV-enabled MEC system. To maximize the computation efficiency of the terminal system, we consider jointly optimizing the terminal's CPU frequency, transmission power, offloading correlation decision, and the 3D position and beamwidth of the UAV. Since the original problem is a mixed-integer nonlinear programming (MINLP) problem with a fractional structure, which is difficult to solve directly. Based on Dinkelbach's method, convex optimization theory, and greedy strategy, we simplify the mathematical model and propose a four-stage alternating iterative computation efficiency maximization algorithm(FICEM) to solve the problem. The simulation results indicate that the algorithm converges fast in various network scenarios and that its computation efficiency is better than that of the baseline algorithm. In addition, the simulation results also manifest the effect of different network parameters on the computation efficiency of the terminal system.
The Internet of Underwater Things (IoUT) has attracted a lot of attention because of its promising applications in underwater environmental monitoring; however, the characteristics of acoustic communication, e.g., long propagation delay and high attenuation, pose great challenges for efficient and reliable underwater data transmission. Currently, opportunistic routing is regarded as a key technology to improve the packet delivery ratio, because it can dynamically choose several forwarding nodes and leverage their cooperative forwarding to increase network throughput. However, choosing an excessive number of forwarding nodes may result in energy waste and lengthy communication delays. Therefore, an Opportunistic Routing based on Directional Transmission (ORDT) is studied to improve packet delivery timeliness and reliability and lower energy consumption. ORDT mainly contains three phases: forwarding area division, candidate forwarder selection, and candidate forwarder coordination. The forwarding region is first established based on directional transmission. Only neighbors located in the forwarding region can forward packets. Following that, candidate forwarders in the forwarding region are chosen depending on their forwarding capability. Additionally, the chosen candidate’s time of holding packets is specified so that they might collaborate to reduce redundant data transmission and transmit packets to gateway nodes. Then, an Autonomous Underwater Vehicle (AUV) is employed to gather packets from gateway nodes. Simulation findings demonstrate that ORDT performs better than existing opportunistic routing in terms of packet delivery success rate, transmission latency, and energy usage.
Since the 1980s, and particularly with the Hopfield model, recurrent neural networks or RNN became a topic of great interest. The first works of neural networks consisted of simple systems of a few neurons that were commonly simulated through analogue electronic circuits. The passage from the equations to the circuits was carried out directly without justification and subsequent formalisation. The present work shows a way to formally obtain the equivalence between an analogue circuit and a neural network and formalizes the connection between both systems. We also show which are the properties that these electrical networks must satisfy. We can have confidence that the representation in terms of circuits is mathematically equivalent to the equations that represent the network.
Conservation of Underwater Cultural Heritage is crucial to preserve society's history. This work proposes a platform based on Internet of Underwater Things technologies and the Edge Computing paradigm. It will incorporate Artificial Intelligence techniques that support the monitoring and management of Underwater Cultural Heritage. These algorithms and models, capable of generating knowledge, will work as a supporting tool for decision-making. The platform will integrate information stored in databases with data acquired in real-time, working independently and in collaboration with other platforms and systems.
With the passage of time, the exploitation of Internet of Things (IoT) sensors and devices has become more complicated. The Internet of Underwater Things (IoUT) is a subset of the IoT in which underwater sensors are used to continually collect data about ocean ecosystems. Predictive analytics can offer useful insights to the stakeholders associated with environmentalists, marine explorers, and oceanographers for decision-making and intelligence about the ocean, when applied to context-sensitive information, gathered from marine data. This study presents an architectural framework along with algorithms as a realistic solution to design and develop an IoUT system to excel in the data state of the practice. It also includes recommendations and forecasting for potential partners in the smart ocean, which assist in monitoring and environmental protection. A case study is implemented which addresses the solution's usability and agility to efficiently exploit sensor data, executes the algorithms, and queries the output to assess performance. The number of trails is performed for data insights for the 60-day collection of sensor data. In the context of the smart ocean, the architectural design innovative ideas and viable approaches can be taken into consideration to develop and validate present and next-generation IoUTs and are simplified in this solution.
Due to the advancement of wireless communications, Internet of Things (IoT) becomes a promising technology in today's digital world. For the enhancement of underwater applications such as ocean exploration, deep-sea monitoring, underwater surveillance, diver network monitoring, location and object tracking, etc., Internet of underwater things (IoUT) has been introduced. However, underwater communication suffers from energy consumption due to fluctuations of the underwater environment and operational factors according to the distributions of objects or vehicles in shallow and deep water. The IoT quality of service (QoS) in underwater communication networks is critically affected by the different energy factors related to networking and the physical layer. Network topology and routing protocol are two important major factors affecting the power consumption of IoUT nodes and vehicles. The clustering approach is considered the best choice for IoUT, however it may suffer from various influences related to the underwater environment. The optimisation-based AI technologies in clustering approaches enable to achieve of energy efficiency for IoUT applications. This paper provides a systematic review of different energy efficiency methodologies for IoUT, and classified them according to the strategies used, in addition to the research gaps in clustering-based approaches, and future directions.
Oceanographic data collection, disaster prevention, aided navigation, critical observation sub-missions, contaminant screening, and seaward scanning are just a few of the submissions that use underwater sensor hubs. Unmanned submerged vehicles (USVs) or autonomous acoustic underwater vehicles (AUVs) through sensors would similarly be able to explore unique underwater resources and gather data when utilized in conjunction with integrated screen operations. The most advanced technological method of oceanic observation is wireless information routing beneath the ocean or generally underwater. Water bottoms are typically observed using oceanographic sensors that collect data at certain ocean zones. Most research on UWSNs focuses on physical levels, even though the localization level, such as guiding processes, is a more recent zone. Analyzing the presenting metrics of the current direction conventions for UWSNs is crucial for considering additional enhancements in a procedure employing underwater wireless sensor networks for locating sensors (UWSNs). Due to their severely constrained propagation, radio frequency (RF) transmissions are inappropriate for underwater environments. This makes it difficult to maintain network connectivity and localization. This provided a plan for employing adequate reliability and improved communication and is used to locate the node exactly using a variety of methods. In order to minimize inaccuracies, specific techniques are utilized to calculate the distance to the destination. It has a variety of qualities, such as limited bandwidth, high latency, low energy, and a high error probability. Both nodes enable technical professionals stationed on land to communicate data from the chosen oceanic zones rapidly. This study investigates the significance, uses, network architecture, requirements, and difficulties of undersea sensors.
We present a review of how reinforcement learning (RL) is helping to tackle some of the most challenging problems in the Internet-of-underwater-things (IoUTs). Scientists estimate that 50-80 percent of atmospheric oxygen comes from the ocean, implying that life on earth depends heavily on clean and healthy oceans. This huge significance of the ocean in supporting life on earth is motivating the use of artificial intelligence (AI) and machine learning (ML) tools to create a sustainable marine ecosystem. We briefly review the RL paradigm, its categorisations and RL algorithms developed to solve important problems in IoUTs. New literature keeps emerging that show innovative applications of RL in underwater communications and networking that far outperform conventional solutions and other ML-based methods. Due to its online learning nature, RL is particularly useful for decision making in dynamic environments such as underwater where the communication channel is stochastic and rapidly varying. We explore the applications of RL in IoUTs, showing different classes of IoUTs problems and high-lighting RL algorithms that are tailored to solving them. Despite the significant progress that has made in the RL field, there are still many challenges and open research problems in the use of RL in IoUTs. We conclude the article with an outline of some of these challenges and suggest some ways forward.
Underwater environments are emerging as a new frontier for data science thanks to an increase in deployments of underwater sensor technology. Challenges in operating computing underwater combined with a lack of high-speed communication technology covering most aquatic areas means that there is a significant delay between the collection and analysis of data. This in turn limits the scale and complexity of the applications that can operate based on these data. In this paper, we develop underwater fog computing support using low-cost micro-clouds and demonstrate how they can be used to deliver cost-effective support for data-heavy underwater applications. We develop a proof-of-concept micro-cloud prototype and use it to perform extensive benchmarks that evaluate the suitability of underwater micro-clouds for diverse underwater data science scenarios. We conduct rigorous tests in both controlled and field deployments, using river and sea waters. We also address technical challenges in enabling underwater fogs, evaluating the performance of different communication interfaces and demonstrating how accelerometers can be used to detect the likelihood of communication failures and determine which communication interface to use. Our work offers a cost-effective way to increase the scale and complexity of underwater data science applications, and demonstrates how off-the-shelf devices can be adopted for this purpose.
Providing qualified and fair communications for underwater wireless sensor networks (UWSNs) has garnered considerable interest in light of scarce resources and dynamic channel conditions. Fairness is critical in various situations, including emergency communications in resource-constrained underwater networks that balance load and energy amongst nodes to optimize network performance. Existing solutions for fair communications, on the other hand, frequently come at the expense of network capacity. This paper focuses on the power management strategy that jointly optimizes the reuse, fairness, and capacity of UWSNs while also proposing a new metric for fair spatial reuse in networks: the fair reuse index. We observe that the fair reuse index for UWSNs is strongly reliant on the network density, channel conditions, and application requirements. As a result, UWSNs commonly exhibit load imbalance and struggle to meet required network lifetimes. Towards this end, we propose DMPM, a Deep Multi-agent reinforcement learning-based Power Management strategy for increasing the fair reuse of UWSNs. DMPM strives to maximize the network’s fair reuse while allowing for gentle network capacity decrease. In two representative communication scenarios, numerical results demonstrate that DMPM achieves a significantly better trade-off between network capacity and fair reuse than baseline techniques. We also construct three reward functions for DMPM and discuss how different reward functions affect node behaviors. Delivery delays of different models are discussed. We hope that the work provided in this study will prove to be invaluable in the design and optimization of UWSNs.
Acoustic tags have been used to monitor the swimming patterns of downstream migrating salmon smolts approaching various dams on the Columbia River, USA. Downstream migrating yearling chinook (Oncorhynchus tshawytscha), steelhead (O. mykiss), sockeye (O. nerka), and sub-yearling chinook smolts were surgically implanted with acoustic tags. Fish were tracked in three-dimensions as they approached and passed into the turbine intakes, spillways, and surface bypass channel entrances at the dams during the spring and summer outmigrations of 2005-2009. A number of advances in the analysis methods, techniques and software have been made over the past several years. Some of these improvements include the development of fish density algorithms, stream trace modeling analysis, and advances in three-dimensional animation programs. Three-dimensional tracks of fish approaching the turbine intakes, spillways, and surface bypass channel entrances will be presented. Concentrations of fish passage will be presented as three-dimensional fish densities superimposed over dam structures.
Large-scale mobile Underwater Wireless Sensor Network (UWSN) is a novel networking paradigm to explore aque- ous environments. However, the characteristics of mobile UWSNs, such as low communication bandwidth, large prop- agation delay, floating node mobility, and high error prob- ability, are significantly different from ground-based wire- less sensor networks. The novel networking paradigm poses inter-disciplinary challenges that will require new techno- logical solutions. In particular, in this article we adopt a top-down approach to explore the research challenges in mo- bile UWSN design. Along the layered protocol stack, we roughly go down from the top application layer to the bot- tom physical layer. At each layer, a set of new design in- tricacies are studied. The conclusion is that building scal- able mobile UWSNs is a challenge that must be answered by inter-disciplinary efforts of acoustic communications, signal processing and mobile acoustic network protocol design.
Anadromous river herring (alewives Alosa pseudoharengus and blueback herring A. aestivalis), which constitute a historically and ecologically important component of coastal rivers, have declined precipitously throughout the Atlantic seaboard. Suggested causes of river herring decline include commercial fishing and predation by striped bass Morone saxatilis. Although the causes of this recent trend are poorly understood, river herring are especially vulnerable to adverse impacts during their spring spawning migration. Radiotelemetry is an especially useful method for addressing potential problems encountered during the movement of these fish from the ocean to freshwater. In spite of frequent calls for evaluation of telemetry methods, controlled tests of posttagging effects are rare for alosids and virtually nonexistent for anadromous river herring. We developed a protocol for gastric tagging of anadromous river herring, and we used hatchery and field studies to evaluate behavior, tag placement, stress response, and posttagging mortality. We also compared tagger effects and quantified posttagging upstream movements of fish in the field. In controlled hatchery trials, no fish died at 10 min, 1 h, or 14 d posttagging. No tags were rejected, and only 1 of 35 tags ruptured the gut. In field cages, mortality, plasma cortisol, glucose, and chloride measured at 24 h were similar between tagged and untagged fish. In the field, 12 of 14 fish moved upriver after tagging and spent 114 h on average at upriver sites. Using a variety of approaches, we found no evidence that our tagging protocol adversely affected river herring in comparison with untagged fish that were subjected only to handling and holding. Our protocol, evaluated by comparing responses of tagged and untagged fish under controlled conditions, may be useful in future studies that seek to understand causes of decline for anadromous river herring.
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.
Wireless sensor networks (WSNs) research has pre-dominantly assumed the use of a portable and limited energy source, viz. batteries, to power sensors. Without energy, a sensor is essentially useless and cannot contribute to the utility of the network as a whole. Consequently, substantial research efforts have been spent on designing energy-efficient networking protocols to maximize the lifetime of WSNs. However, there are emerging WSN applications where sensors are required to operate for much longer durations (like years or even decades) after they are deployed. Examples include in-situ environmental/habitat monitoring and structural health monitoring of critical infrastructures and buildings, where batteries are hard (or impossible) to replace/recharge. Lately, an alternative to powering WSNs is being actively studied, which is to convert the ambient energy from the environment into electricity to power the sensor nodes. While renewable energy technology is not new (e.g., solar and wind) the systems in use are far too large for WSNs. Those small enough for use in wireless sensors are most likely able to provide only enough energy to power sensors sporadically and not continuously. Sensor nodes need to exploit the sporadic availability of energy to quickly sense and transmit the data. This paper surveys related research and discusses the challenges of designing networking protocols for such WSNs powered by ambient energy harvesting.
Two powerful trends in marine technology (autonomous assets and distributed sensing) are combining to create a dramatic pressure on the underwater (UW) communications industry to provide much less expensive modems with interoperable capability that can form ad-hoc networks. Currently, UW modem manufacturers use proprietary schemes that are mutually unintelligible, even if using the same frequency band. This can be regarded as a language issue, akin to different cultures each speaking their mother tongue and no other, despite the fact that the coding and transmission software and hardware (brain and vocal tract), as well as the reception and decoding (ears and brain), are largely similar between different cultures. We need a common language, which could be chosen by rational design (e.g. Esperanto) or by de-facto practicality (e.g. English). The difficulties associated with reaching large-scale consensus on standards suggest that we are more likely to see the latter process dominate. The lingua-franca that emerges may not be the most efficient, but it will have the property that it is simple enough to master at a basic working level, sufficient to achieve simple functionality from which more optimal choices can perhaps be bootstrapped. This paper describes such a standard, JANUS, being developed and promoted at NURC in collaboration with a network of international academia, research centres and companies. Similarly, NURC is pursuing related work on Media Access Control (MAC), Delay and Disruption-Tolerant Network (DTN) protocols and low-overhead routing, all of which are key components of ad-hoc networking. NURC is also actively engaged in communication architecture design (particularly to support cross-layer connectivity), performance metrics, realistic simulation capabilities, standardizing channel modelling and establishing canonical problems to test candidate protocols. There are many tasks, and NURC is too small to make a significant impact alone. NURC is theref-
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ore pursuing a role as a multi-national, commercially-neutral hub, drawing together stakeholders and acting as a catalyzing agent for international collaborative efforts to move these solutions forward for the whole community.
Delay and Disruption tolerant networking (DTN) embraces the concepts of occasionally-connected networks that may suffer from frequent partitions and that may be comprised of more than one divergent set of protocols or protocol families. Since DTN was conceived to relax most of the assumptions associated with Internet protocols, the most important of which is the availability of an end-to-end path between source and destination for the duration of a communication session, it is possible to envision the application of DTN concepts to under-water acoustic networks, where the bandwidth-limited acoustic channel suffers frequent disruptions due to environmental factors. This paper presents the design and implementation of an Underwater Convergence Layer (UCL) for the DTN2 Reference Implementation, which provides DTN support for the WHOI Micro-Modem. UCL was tested in the field during the Acommsnet10 sea trial, in a heterogeneous context comprising underwater nodes communicating acoustically and surface nodes communicating with radio frequency. Initial results and lessons learned from field testing are also presented. The principal value of this development resides in the delivery of new capabilities towards the application of DTN concepts to the maritime domain, to enable functionalities like multi-hop acoustic communication, data mule using autonomous vehicles and gateways between different transmission media (e.g. between underwater acoustic communications and above water radio/satellite).
This article presents the design challenges posed by a new class of ultra-low-power devices referred to as Energy-Harvesting Active Networked Tags (EnHANTs). EnHANTs are small, flexible, and self-reliant (in terms of energy) devices that can be attached to objects that are traditionally not networked (e.g., books, furniture, walls, doors, toys, keys, produce, and clothing). EnHANTs will enable the Internet of Things by providing the infrastructure for various novel tracking applications. Examples of these applications include locating misplaced items, continuous monitoring of objects, and determining locations of disaster survivors. Recent advances in ultra-low-power circuit design, ultra-wideband (UWB) wireless communications, and organic energy harvesting techniques will enable the realization of EnHANTs in the near future. The harvesting components and the ultra-low-power physical layer have special characteristics whose implications on the higher layers have yet to be studied (e.g., when using UWB communications, the energy required to receive a bit is significantly higher than the energy required to transmit a bit). In this article, we describe paradigm shifts associated with technologies that enable EnHANTs and demonstrate their implications on higher-layer protocols. Moreover, we describe some of the components we have designed for EnHANTs. Finally, we briefly discuss our indoor light measurements and their implications on the design of higher-layer protocols.
Most underwater wireless networks use acoustic waves as the transmission medium nowadays, but the chances of getting much more out of acoustic modems are quite remote. Optical links are impractical for many underwater applications. Given modern operational requirements and digital communications technology, the time is now ripe for re-evaluating the role of electromagnetic signals in underwater environments. The research presented in this article is motivated by the limitations of current and established wireless underwater techniques, as well as the potential that electromagnetic waves can offer to underwater applications. A case study is presented that uses electromagnetic technology in a small-scale underwater wireless sensor network. The results demonstrate the likely effectiveness of the designated network.
Underwater sensor networks (UWSNs) have been proposed for many location-dependent applications such as oceanographic data collection, pollution monitoring, mine reconnaissance, etc. Accurate node localization plays an important role in realizing the potential gains of these applications. Although many localization algorithms have been proposed for terrestrial sensor networks in recent years, it is not feasible to directly use these algorithms in UWSNs since UWSNs lack a fast and reliable communication channel. Further, due to their slow convergence speeds and high communication overhead, distributed localization algorithms designed for small-scale UWSNs are not practical for large-scale underwater sensor systems. To achieve accurate and energy efficient node localization in large-scale UWSNs, an asymmetrical round trip based localization (ARTL) algorithm is proposed in this paper. This algorithm has low computational complexity and excellent scalability. Without time synchronization, this algorithm can achieve highly accurate ranging in large-scale UWSNs. Simulation results demonstrate the effectiveness of our design in terms of both localization accuracy and energy consumption.
Underwater multimedia acoustic sensor networks will enable new underwater applications such as multimedia coastal and tactical surveillance, undersea explorations, picture and video acquisition and classification, and disaster prevention. Because of the different application requirements, there is a need to provide differentiated-service support to delay-sensitive and delay-tolerant data traffic as well as to loss-sensitive and loss-tolerant traffic. While research on underwater communication protocol design so far has followed the traditional layered approach originally developed for wired networks, improved performance can be obtained with a cross-layer design. Hence, the objective of this work is twofold: (1) study the interactions of key underwater communication functionalities such as modulation, forward error correction, medium access control, and routing; and (2) develop a distributed cross-layer communication solution that allows multiple devices to efficiently and fairly share the bandwidth-limited high-delay underwater acoustic medium.
This paper describes the implementation of a novel prototypical underwater augmented reality (UWAR) system that provides visual aids to increase commercial divers' capability to detect, perceive, and understand elements in underwater environments. During underwater operations, a great amount of stress is imposed on divers by environmental and working conditions such as pressure, visibility, weightlessness, current, etc. Those factors cause a restriction in divers' sensory inputs, cognition and memory, which are essentials for locating within the surroundings and performing their task effectively. The focus of this research was to improve some of those conditions by adding elements in divers' views in order to increase awareness and safety in commercial diving operations. We accomplished our goal by assisting divers in locating the work site, keeping informed about orientation and position (constantly), and providing a 3D virtual model for an assembling task. The system consisted of a video see-through head mounted display (HMD) with a Web cam in front of it, protected by a custom waterproof housing placed over the diving mask. As a very first step, optical square-markers were used for positioning and orientation tracking purposes (POSE). The tracking was implemented with a ubiquitous-tracking software (Ubitrack). Finally, we discuss the possible implications of a diver-machine synergy.
Underwater sensor nodes will find applications in oceanographic data collection, pollution monitoring, offshore exploration, disaster prevention, assisted navigation and tactical surveillance applications. Moreover, unmanned or autonomous underwater vehicles (UUVs, AUVs), equipped with sensors, will enable the exploration of natural undersea resources and gathering of scientific data in collaborative monitoring missions. Underwater acoustic networking is the enabling technology for these applications. Underwater networks consist of a variable number of sensors and vehicles that are deployed to perform collaborative monitoring tasks over a given area.In this paper, several fundamental key aspects of underwater acoustic communications are investigated. Different architectures for two-dimensional and three-dimensional underwater sensor networks are discussed, and the characteristics of the underwater channel are detailed. The main challenges for the development of efficient networking solutions posed by the underwater environment are detailed and a cross-layer approach to the integration of all communication functionalities is suggested. Furthermore, open research issues are discussed and possible solution approaches are outlined.
Water quality monitoring and forecasting plays an important role in modern intensive fish farming management. This paper describes an online water quality monitoring system for intensive fish culture in China, which combined web-server-embedded technology with mobile telecommunication technology. Based on historical data, this system is designed to forecast water quality with artificial neural networks (ANNs) and control the water quality in time to reduce catastrophic losses. The forecasting model for dissolved oxygen half an hour ahead has been validated with experimental data. The results demonstrate that multi-parametric, long-distance and online monitoring for water quality information can be accurately acquired and predicted by using this established monitoring system.
Effective solutions should be devised to handle the effects of shadow zones in Underwater Wireless Sensor Networks (UWSNs). An adaptive topology reorganization scheme that maintains connectivity in multi-hop UWSNs affected by shadow zones has been developed in the context of two Spanish-funded research projects. A mathematical model has been proposed to find the optimal location for sensors with two objectives: the minimization of the transmission loss and the maintenance of network connectivity. The theoretical analysis and the numerical evaluations reveal that our scheme reduces the transmission loss under all propagation phenomena scenarios for all water depths in UWSNs and improves the signal-to-noise ratio.
This paper puts the Internet of Things in a wider context: How it relates to the Future Internet overall, and where the business value lies so that it will become interesting for enterprises to invest in it. Real-World Awareness and Business Process Decomposition are the two major paradigms regarding future business value. The major application domains where the Internet of Things will play an important role and where there are concrete business opportunities are highlighted. But there are also many technical challenges that need to be addressed. These are listed and it is shown how they are tackled by existing research projects with industrial participation.
We propose a distributed mechanism, Dis-VoW, to detect wormhole attacks in under-water sensor networks. In Dis-VoW, every sensor reconstructs local network layout using multi-dimensional scaling. It detects the wormholes by visualising the distortions in edge lengths and angles among neighbouring sensors. The contributions include:
This paper examines the main approaches and challenges in the design and implementation of underwater wireless sensor networks. We summarize key applications and the main phenomena related to acoustic propagation, and discuss how they affect the design and operation of communication systems and networking protocols at various layers. We also provide an overview of communications hardware, testbeds and simulation tools available to the research community.
In this paper, we propose a novel distributed localization scheme LDB, a 3D localization scheme with directional beacons for Underwater Acoustic Sensor Networks (UWA-SNs). LDB localizes sensor nodes using an Autonomous Underwater Vehicle (AUV) as a mobile beacon sender. Mounted with a directional transceiver which creates conical shaped directional acoustic beam, the AUV patrols over the 3D deployment volume with predefined trajectory sending beacons with constant interval towards the sensor nodes. By listening two or more beacons sent from the AUV, the nodes can localize themselves silently. Through theoretical analysis, we provide the upper bound of the estimation error of the scheme. We also evaluate the scheme by simulations and the results show that our scheme can achieve a high localization accuracy, even in sparse networks.
Fish display robust neuroendocrine and physiologic stress responses to noxious stimuli. Many anesthetic, sedative, or analgesic drugs used in other vertebrates reduce stress in fish, decrease handling trauma, minimize movement and physiologic changes in response to nociceptive stimuli, and can be used for euthanasia. But extrapolating from limited published anesthetic and sedative data to all fish species is potentially harmful because of marked anatomic, physiologic, and behavioral variations; instead, a stepwise approach to anesthetizing or sedating unfamiliar species or using unproven drugs for familiar species is advisable. Additionally, knowledge of how water quality influences anesthesia or sedation helps limit complications. The most common method of drug administration is through immersion, a technique analogous to gaseous inhalant anesthesia in terrestrial animals, but the use of injectable anesthetic and sedative agents (primarily intramuscularly, but also intravenously) is increasing. Regardless of the route of administration, routine preprocedural preparation is appropriate, to stage both the animals and the supplies for induction, maintenance, and recovery. Anesthetic and sedation monitoring and resuscitation are similar to those for other vertebrates. Euthanasia is most commonly performed using an overdose of an immersion drug but injectable agents are also effective. Analgesia is an area in need of significant research as only a few studies exist and they provide some contrasting results. However, fish have mu and kappa opiate receptors throughout the brain, making it reasonable to expect some effect of at least opioid treatments in fish experiencing noxious stimuli.
Ehrenberg, J. E., and Steig, T. W. 2009. A study of the relationship between tag-signal characteristics and achievable performances in acoustic fish-tag studies. – ICES Journal of Marine Science, 66: 1278–1283.
Acoustic tags have been used in fish-behaviour studies in a variety of marine and freshwater environments. The intended objectives of these studies vary widely. In some cases, they require accurate three-dimensional tracking of the individual fish locations. In other cases, tags are used for estimating fish survival along a migration route. There are varieties of schemes that have been proposed and used for implementing tag systems. The purpose of this paper is to explain the relationship between the various characteristics of acoustic signals transmitted by the tags and the tag-system performance that can be achieved. In particular, the ranges at which the tags can be detected and uniquely identified, the positional accuracy, and the number of unique codes that can be assigned to individual fish are all functions of the signal type. This paper demonstrates that when the pulse-repetition period is used to encode the tag identification, the range performance for the tag is superior to that achieved using a scheme that has binary-encoded bits as part of the transmitter signal. The parametric results presented will assist investigators in their selection of the type of acoustic tags or tag parameters needed to achieve the objectives of acoustic fish-tag studies.
The World Wide Web has succeeded in large part because its software architecture has been designed to meet the needs of an Internet-scale distributed hypermedia application. The modern Web architecture emphasizes scalability of component interactions, generality of interfaces, independent deployment of components, and intermediary components to reduce interaction latency, enforce security, and encapsulate legacy systems. In this article we introduce the Representational State Transfer (REST) architectural style, developed as an abstract model of the Web architecture and used to guide our redesign and definition of the Hypertext Transfer Protocol and Uniform Resource Identifiers. We describe the software engineering principles guiding REST and the interaction constraints chosen to retain those principles, contrasting them to the constraints of other architectural styles. We then compare the abstract model to the currently deployed Web architecture in order to elicit mismatches between the existing protocols and the applications they are intended to support.
With the increment of the fishery products in China, more and more attention is drawn to the safety of farming fishery products from different levels. China always stressed the importance to the issue of food safety. The wide application of RFID and other technology offers great support to the upgrading of the safety level of fishery products. The paper firstly introduces the application principle of RFID and the five steps from producing area to table of farming fishery products. Then it analyzes the role in the safety risk decrease of farming fishery products that is played by the application of RFID. Finally, it puts forward that the application of RFID can combine the realtime control and feedback control together and therefore can improve the safety level of fishery products in China.
Acoustic communication in Underwater Wireless Communication Networks (UWCNs) has several challenges due to the presence of fading, multipath and refractive properties of the sound channel which necessitate the development of precise underwater channel models. Some existing channel models are simplified and do not consider multipath or multipath fading. In this paper, a detailed survey on ray-theory-based multipath Rayleigh underwater channel models for underwater wireless communication is presented and the research challenges for an efficient communication in this environment are outlined. These channel models are valid for shallow or deep water. They are based on acoustic propagation physics which captures different propagation paths of sound in the underwater and consider all the effects of shadow zones, multipath fading, operating frequency, depth and water temperature. The propagation characteristics are shown through mathematical analysis. Transmission losses between transceivers are investigated through simulations. Further simulations are carried out to study the bit error rate effects and the maximum internode distances for different networks and depths considering a 16-QAM modulation scheme with OFDM as the multicarrier transmission technique. The effect of weather season and the variability of ocean environmental factors such as water temperature on the communication performance are also shown. The mathematical analysis and simulations highlight important considerations for the deployment and operation of UWCNs.
In the project "RFID from Farm to Fork" an implementation of RFID technologies will be used along the food supply chain: from farm to the consumer. The paper is intended to highlight two examples of how to define farmed fish traceability system suitable for small and medium sized enterprises (SMEs). The first one presents a change from a manual collection of data to an electronic RFID implementation in a small company that performs a complete supply chain from fish farm to retail and private customers. In the second one, a part of already automated process of packing fish using barcode labeling will be upgraded by RFID technology, and traceability will be extended back to breeding and on-growing fish farms, which currently use manual collection of data. The proposed design and selection of fixed and mobile RFID readers in different steps of pilot implementation are defined as modules which could be used as a general approach to apply an automated business process.
Given a number of patrollers that are required to detect an intruder in a channel, the channel patrol problem consists of determining the periodic trajectories that the patrollers must trace out so as to maximized the probability of detection of the intruder. We formulate this problem as an optimal control problem. We assume that the patrollers' sensors are imperfect and that their motions are subject to turn-rate constraints, and that the intruder travels straight down a channel with constant speed. Using discretization of time and space, we approximate the optimal control problem with a large-scale nonlinear programming problem which we solve to obtain an approximately stationary solution and a corresponding optimized trajectory for each patroller. In numerical tests for one, two, and three underwater patrollers, an underwater intruder, different trajectory constraints and several intruder speeds, we obtain new insight--not easily obtained using simply geometric calculations--into efficient patrol trajectory design for multiple patrollers in a narrow channel where interaction between the patrollers is unavoidable due to their limited turn rate.
Three examples of inter-agency cooperation utilizing current generation, individual Autonomous Underwater Vehicles (AUVs) are described consistent with recent recommendations of the U.S. Commission on Ocean Policy. The first steps in transforming individual AUVs into adaptive, networked systems are underway. To realize an affordable and deployable system, a network-class AUV must be designed with cost-size constraints not necessarily applied in developing solo AUVs. Vehicle types are suggested based on function and ocean operating regime: surface layer, interior and bottom layer. Implications for platform, navigation and control subsystems are explored and practical formulations for autonomy and intelligence are postulated for comparing performance and judging behavior. Laws and conventions governing intelligent maritime navigation are reviewed and an autonomous controller with conventional collision avoidance behavior is described. Network-class cost constraints can be achieved through economies of scale. Productivity and efficiency in AUV manufacturing will increase if constructive competition is maintained. Constructive strategies include interface and operating standards. Professional societies and industry trade groups have a leadership role to play in establishing public, open standards.
Underwater wireless communication networks are particularly vulnerable to malicious attacks due to the high bit error rates, large and variable propagation delays, and low bandwidth of acoustic channels. The unique characteristics of the underwater acoustic communication channel, and the differences between underwater sensor networks and their ground-based counterparts require the development of efficient and reliable security mechanisms. In this article, a complete survey of security for UWCNs is presented, and the research challenges for secure communication in this environment are outlined.
Underwater acoustic sensor networking is the enabling technology for a wide range of applications including naval surveillance, oil platform monitoring, earthquake and tsunami forewarning, climate and ocean observation, and water pollution tracking. Underwater sensor nodes with sensing and communication capabilities form the underwater acoustic sensor network. Localizing the underwater sensor nodes is one of the fundamental tasks for UASNs where the location information can be used in data tagging, routing, and node tracking. Localization for UASNs is an active research topic where a large number of techniques have been proposed recently. This article provides an up-to-date survey of these techniques while pointing out the open issues.
This paper provides an in-depth view on nanosensor technology and electromagnetic communication among nanosensors. First, the state of the art in nanosensor technology is surveyed from the device perspective, by explaining the details of the architecture and components of individual nanosensors, as well as the existing manufacturing and integration techniques for nanosensor devices. Some interesting applications of wireless nanosensor networks are highlighted to emphasize the need for communication among nanosensor devices. A new network architecture for the interconnection of nanosensor devices with existing communication networks is provided. The communication challenges in terms of terahertz channel modeling, information encoding and protocols for nanosensor networks are highlighted, defining a roadmap for the development of this new networking paradigm.
The underwater environment is widely regarded as one of the most difficult communication channels. Underwater acoustic communications systems are challenged by the characteristics of acoustic propagation through the underwater environment. There are a wide range of physical processes that impact underwater acoustic communications and the relative importance of these processes are different in different environments. In this paper some relevant propagation phenomena are described in the context of how they impact the development and/or performance of underwater acoustic communications networks. The speed of sound and channel latency, absorption and spreading losses, waveguide effects and multipath, surface scattering, bubbles, and ambient noise are all briefly discussed.
We introduce and study the localization problem in large scale underwater acoustic sensor networks. Considering that depth information is typically available for underwater sensors, we transform the 3D underwater positioning problem into its two-dimensional counterpart via a projection technique. We then introduce a localization scheme specifically designed for large scale acoustic underwater sensor networks. The proposed localization scheme does not require time-synchronization in the network. This scheme relies on time-differences of arrival (TDoA) measured locally at a sensor to detect range differences from the sensor to three anchors that can mutually hear each other. We consider variations in the speed of sound and analyze the performance of the proposed scheme in terms of the number of localized nodes, location errors, and the number of reference nodes.
Anti-submarine warfare(ASW) is a critical challenge for maintaining a fleet presence in hostile areas. Technology advancement has allowed submarines to evade standard sonar detection. A viable alternative is to place magnetic or acoustic sensors in close proximity to possible underwater pathways of submarines. This approach may require deploying large-scale underwater sensor networks to form 3-dimensional barriers. We present new results on sensor barriers for 3-dimensional sensor networks. We first show that when sensor locations follow a Poisson Point Process then sensor barriers in a large 3- dimensional fixed emplacement sensor field are unlikely to exist. We use the notion of 3-dimensional stealth distance to measure how far a submarine can travel in a sensor network without being detected. We devise an energy-conserving scheme to construct 3- dimensional barriers using mobile sensors. We focus on developing an energy efficient matching of mobile sensors to cover grid points using distributed auction algorithms. Specifically, we try to minimize the maximum travel distance between any sensor and its assigned grid point. Through simulation we show in comparison to the optimal solution, the distributed auction based approach offers reduced computation time and similar maximum travel distance. This provides a promising new approach to constructing barriers in 3-dimensional sensor networks.
In this article, we present the current status of the Internet of Things, and discuss how the current situation of many "Intranets" of Things should evolve into a much more integrated and heterogeneous system. We also summarize what in our opinion are the main wirelessand mobility-related technical challenges that lie ahead, and outline some initial ideas on how such challenges can be addressed in order to facilitate the IoT's development and acceptance in the next few years. We also describe a case study on the IoT protocol architecture.
Machine-to-machine (M2M) communications is a new and rapidly developing technology for large-scale networking of devices without dependence on human interaction. Energy efficiency is one of the important design objectives for machine-to-machine network architectures that often contain multi-hop wireless subnetworks. Constructing energy-efficient routes for sending data through such networks is important not only for the longevity of the nodes which typically depend on battery energy, but also for achieving an environmentally friendly system design overall, which will be imperative as M2M networks scale in number of nodes as projected. The objective of this survey is to provide a comprehensive look into shortest-path based energy-efficient routing alternatives to provide a reference for system designers as well as researchers. We start by describing M2M and its application areas, as well as its challenges. Next, a detailed account of energy-efficient unicast routing alternatives, with a particular focus on those based on additive link cost is given. Following a novel comprehensive classification of shortest-path-based energy-efficient routing algorithms designed for wireless ad hoc and sensor networks, we end by comparisons and discussions of the use of different cost metrics.
With technological advances there are many physical objects that are designed in digital format, some examples are: books, agendas, tickets, etc. One of the characteristics of digital objects is that each type of object has its own format, in most cases each object type can only be interpreted by a particular application, so will have problems to be interpreted. Internet of things (IoT) promotes the integration and communication between physical objects, including digital objects on the IoT can automate and streamline many tasks. The absence of common format for digital objects also causes problems of interaction and communication. There is no standardized way to obtain the actions or services associated with the digital object, which makes it difficult for these digital objects to interact and integrate in a generic way with other applications, devices or embedded systems. Based on the problems identified in this document a proposal is detailed in search for a single structure and for the construction of any digital object. The validity of the approach has been verified through a prototype system working with real appliances.
Abstract This paper reviews the physical fundamentals and engineering implementations,for efficient information exchange via wireless communication,using physical waves as the carrier among,nodes in an underwater sensor network. The physical waves under discussion include sound, radio, and light. We first present the fundamental physics of different waves; then we discuss and compare the pros and cons for adopting different communication carriers (acoustic, radio, and optical) based on the fundamental first principles of physics and engineering practice. The discussions are mainly targeted at underwater sensor networks with densely deployed nodes. Based on the comparison study, we make recommendations,for the selection of communication,carriers for underwater sensor networks with engineering countermeasures,that can possibly enhance the communication,efficiency in specified underwater environments. Index Terms Underwater sensor networks, wireless communication, acoustic waves, electromagnetic waves, optical waves.
As an emerging technique, underwater sensor network (UWSN) will enable a wide range of aquatic applications. However, due to the adverse underwater environmental conditions as well as some system constraints, an underwater sensor network is usually viewed as an intermittently connected network (ICN) (or delay/disruption tolerant network (DTN)), which requires specialized routing protocols. Moreover, applications may have different requirements for different types of messages, as demands a smart protocol to handle packets adaptively. In this paper, we propose a novel routing protocol where routing is performed adaptively based on the types of messages and application requirements. This is obtained by exploiting message redundancy and resource reallocation