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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.
... Recent years have witnessed unprecedented developments of maritime technologies including unmanned underwater vehicles (UUVs) and underwater buoy platforms [1]. Such advancements have facilitated numerous civilian/military applications such as ocean exploration and tactical surveillance [1], [2]. ...
... Recent years have witnessed unprecedented developments of maritime technologies including unmanned underwater vehicles (UUVs) and underwater buoy platforms [1]. Such advancements have facilitated numerous civilian/military applications such as ocean exploration and tactical surveillance [1], [2]. To guarantee timely backhauling of the measurement data, establishing communication links between underwater and airborne relaying platforms, i.e., water-air links, can be mandatory, especially for high-sea scenarios, where the longshore stations are too distant to support direct transmission. ...
The escalating interests on underwater exploration/reconnaissance applications have motivated high-rate data transmission from underwater to airborne relaying platforms, especially under high-sea scenarios. Thanks to its broad bandwidth and superior confidentiality, Optical wireless communication has become one promising candidate for water-air transmission. However, the optical signals inevitably suffer from deviations when crossing the highly-dynamic water-air interfaces in the absence of relaying ships/buoys. To address the issue, this article proposes one novel beam alignment strategy based on deep reinforcement learning (DRL) for water-air direct optical wireless communications. Specifically, the dynamic water-air interface is mathematically modeled using sea-wave spectrum analysis, followed by characterization of the propagation channel with ray-tracing techniques. Then the deep deterministic policy gradient (DDPG) scheme is introduced for DRL-based transceiving beam alignment. A logarithm-exponential (LE) nonlinear reward function with respect to the received signal strength is designed for high-resolution rewarding between different actions. Simulation results validate the superiority of the proposed DRL-based beam alignment scheme.
... IoT devices can often collect information via small single-board computers' sensors and share the data after edge computing and data analysis [1]. The Internet of Underwater Things (IoUT) is a network structure composed of several interconnected sensors that can be used to achieve underwater detection, environmental monitoring, and oceanic disaster prediction [2]. ...
... In general, typhoon wave prediction methods can be divided into the following three types: (1) empirical methods based on statistics regression or experience used for rapid initial predictions, such as the SMB method [8]; (2) hydrodynamic models based on physical ...
Huge waves caused by typhoons often induce severe disasters along coastal areas, making the effective prediction of typhoon-induced waves a crucial research issue for researchers. In recent years, the development of the Internet of Underwater Things (IoUT) has rapidly increased the prediction of oceanic environmental disasters. Past studies have utilized meteorological data and feedforward neural networks (e.g., BPNN) with static network structures to establish short lead time (e.g., 1 h) typhoon wave prediction models for the coast of Taiwan. However, sufficient lead time for prediction remains essential for preparedness, early warning, and response to minimize the loss of lives and properties during typhoons. The aim of this research is to construct a novel long lead time typhoon-induced wave prediction model using Long Short-Term Memory (LSTM), which incorporates a dynamic network structure. LSTM can capture long-term information through its recurrent structure and selectively retain necessary signals using memory gates. Compared to earlier studies, this method extends the prediction lead time and significantly improves the learning and generalization capability, thereby enhancing prediction accuracy markedly.
... In oceans and seas, the Internet of Maritime Things (IoMT) is also an excellent example of an IoRT environment [23,24] where, for example, sensors on ships can transmit vital data, facilitating weather forecasts and enhancing maritime safety [25]. Specialized IoRT approaches are also required for the Internet of Underground Things (IoUT), which is applicable to subterranean operations such as mining [26][27][28], and the Internet of Underwater Things (IoUwT), which is applicable to marine exploration or aquaculture [29][30][31][32]. ...
... Monitor and maintain underground infrastructure, including pipelines, tunnels, and power lines, to prevent leaks, collapses, and outages, ensuring public safety and infrastructure reliability. [29][30][31][32] Internet of Underwater Things (IoUwT) ...
The Internet of Things (IoT) is gaining popularity and market share, driven by its ability to connect devices and systems that were previously siloed, enabling new applications and services in a cost-efficient manner. Thus, the IoT fuels societal transformation and enables groundbreaking innovations like autonomous transport, robotic assistance, and remote healthcare solutions. However, when considering the Internet of Remote Things (IoRT), which refers to the expansion of IoT in remote and geographically isolated areas where neither terrestrial nor cellular networks are available, internet connectivity becomes a challenging issue. Non-Terrestrial Networks (NTNs) are increasingly gaining popularity as a solution to provide connectivity in remote areas due to the growing integration of satellites and Unmanned Aerial Vehicles (UAVs) with cellular networks. In this survey, we provide the technological framework for NTNs and Remote IoT, followed by a classification of the most recent scientific research on NTN-based IoRT systems. Therefore, we provide a comprehensive overview of the current state of research in IoRT and identify emerging research areas with high potential. In conclusion, we present and discuss 3GPP’s roadmap for NTN standardization, which aims to establish an energy-efficient IoRT environment in the 6G era.
... Marine data ecosystems may enable the knowledge extraction from the data to provide additional value and create collaboration among ecosystem participants [9], [10]. However, data sharing in this context presents socio-technical challenges such as high costs associated with data acquisition operations [11], risks of national security, business information disclosure, or lack of data quality and interoperability [10]. ...
... These systems present technical challenges typical in land-based IoT systems such as limited battery and computational resources. Beyond these, other challenges arise from the underwater environment where the data is acquired, namely, restricted wireless bandwidth that is also prone to errors and the cost of maintenance and access to the sensor systems [11], [18]. ...
... In the marine domain, data collection has been driven by the specific requirements of individual use cases [12], i.e., data is collected independently without considering the need of other use cases. Given the high costs associated with the data collection process [13]- [15], it is essential to maximize the reuse of in-situ marine data. Adopting data ecosystems is a viable solution to achieve that goal. ...
... 2) Common in-situ marine data errors: In-situ marine data is prone to contamination due to low-power batteries and biofouling, leading to unexpected measurement results [13], [40] The degree to which data has attributes that correctly represent the true value of the intended attribute of a concept or event in a specific context of use. ...
... The emergence of Underwater IoT (UIoT) has garnered significant attention in recent years [11], stimulating research across various related domains, including research on underwater unmanned vehicles [12], underwater wireless sensor networks [13] and marine science [14]. In [15], we propose a new low-power and environmentally friendly underwater data acquisition solution, which leverages Analog Joint Source-Channel Coding (AJSCC) [16] and correlation-aware Hybrid Automatic Repeat Request (HARQ) [17], providing a framework for underwater WSNs that minimize retransmissions and conserve energy and time. ...
... [1][2][3][4][5] Traditional methods for nearshore marine water quality monitoring rely on manual sampling and monitoring. [6] However, these methods are hindered by complex weather conditions and sea state environments, necessitating a significant workforce and specialized equipment, resulting in low efficiency, poor real-time performance, and limited monitoring coverage. Intelligent ocean sensors have emerged with the progression of the Internet of Things (IoTs) technology and ocean engineering. ...
With the rapid evolution of emerging technologies like artificial intelligence, Internet of Things, big data, robotics, and novel materials, the landscape of global ocean science and technology is undergoing significant transformation. Ocean wave energy stands out as one of the most promising clean and renewable energy sources. Triboelectric nanogenerators (TENGs) represent a cutting‐edge technology for harnessing such random and ultra‐low frequency energy toward blue energy. A high‐performance TENG incorporating a double‐spiral zigzag‐origami structure is engineered to achieve continuous sensing and signal transmission in marine environment. Integrating the double‐spiral origami into the TENG system enables efficient energy harvesting from the ocean waves by converting low‐frequency wave vibrations into high‐frequency motions. Under the water wave triggering of 0.8 Hz, the TENG generates a maximum peak power density of 55.4 W m ⁻ ³ , and a TENG array with six units can generate an output current of 375.2 μA (density of 468.8 mA m ⁻ ³ ). This power‐managed TENG array effectively powers a wireless water quality detector and transmits signals without an external power supply. The findings contribute to the development of sustainable and renewable energy technologies for oceanic applications and open new pathways for designing advanced materials and structures in the field of energy harvesting.
... This means that data is often collected in isolation, without considering the potential usefulness for other applications (DQ dimensions Format, Ease of Understanding, Interpretability) [162]. Since collecting data in the marine environment can be quite expensive, it is crucial to make the most of in-situ marine data by using it for multiple purposes (DQ dimensions Format, Interpretability, Usability, Accuracy, Completeness) [163], [164] to share data and information across domains and platforms. ...
Digital Earth (DE), a technology offering real-time visualisation of Earth’s processes, has shown promising results in aiding decision-making for a sustainable world, raising awareness about individual impacts on our planet, and supporting the United Nations Sustainable Development Goals (UN SDGs) agenda. However, both DE and SDGs face a common obstacle: Data Quality (DQ). This review investigates the challenge of DQ in the context of DE for SDGs and explores how IoT can address this challenge and extend the reach of DE to support SDGs. Furthermore, the study discusses three core aspects; first, the potential of IoT as a data source that supplements satellite data for DE for SDGs, second, the DQ challenge that is specific to an IoT-enabled DE for SDGs illustrated through scenarios identified from the literature, and third, solutions and perspectives that address the DQ challenge. This study underscores the necessity of addressing the DQ challenge and discusses some potential solutions to foster effective interdisciplinary collaboration, knowledge sharing, and data reusability. The study provides a viewpoint for understanding and addressing the DQ challenge for an IoT-enabled DE for SDGs to support the UN SDGs agenda for a sustainable world by 2030.
... European research strategy states: "Strengthening observation and monitoring capacities through enabling technologies, new platforms and sensors; addressing undersampling, and ensuring that new environmental parameters can be rapidly and accurately measured" [2]. Furthermore, the Internet of Underwater Things (IoUT), a marine version of the Internet of Things (IoT, [3]) addresses these topics of automation, low power, low cost and smart sensors [4]. Key enabling elements for IoUT are automated and smart devices connected through wireless communication and a common data acquisition and data handling platform, enabling data fusion and machine learning. ...
The rapid growth of marine industries has emphasized the focus on environmental impacts for all industries, as well as the influence of key environmental parameters on, for instance, offshore wind or aquaculture performance, animal welfare and structural integrity of different constructions. Development of automatized sensors together with efficient communication and information systems will enhance surveillance and monitoring of environmental processes and impact. We have developed a modular Smart Ocean observatory, in this case connected to a large-scale marine aquaculture research facility. The first sensor rigs have been operational since May 2022, transmitting environmental data in near real-time. Key components are Acoustic Doppler Current Profilers (ADCPs) for measuring directional wave and current parameters, and CTDs for redundant measurement of depth, temperature, conductivity and oxygen. Communication is through 4G network or cable. However, a key purpose of the observatory is also to facilitate experiments with acoustic wireless underwater communication, which are ongoing. The aim is to expand the system(s) with demersal independent sensor nodes communicating through an “Internet of Underwater Things (IoUT)”, covering larger areas in the coastal zone, as well as open waters, of benefit to all ocean industries. The observatory also hosts experiments for sensor development, biofouling control and strategies for sensor self-validation and diagnostics. The close interactions between the experiments and the infrastructure development allow a holistic approach towards environmental monitoring across sectors and industries, plus to reduce the carbon footprint of ocean observation. This work is intended to lay a basis for sophisticated use of smart sensors with communication systems in long-term autonomous operation in remote as well as nearshore locations.
... The aquatic environment significantly affects the performance and reliability of the network. Underwater networks are characterised as complex and dynamic, with high levels of noise, high-delay channels, and sparse and mobile node deployment [8]. Furthermore, underwater communication devices are typically battery-powered, and no efficient methods currently exist for frequently recharging or replacing these batteries. ...
The Internet of Underwater Things (IoUT) represents an emerging and innovative field with the potential to revolutionize underwater exploration and monitoring. Despite its promise, IoUT faces significant challenges related to reliability and security, which hinder its development and deployment. A particularly critical issue is the establishment of trustworthy communication networks, necessitating the adaptation and enhancement of existing models from terrestrial and marine systems to address the specific requirements of IoUT. This work explores the problem of dishonest recommendations within trust modelling systems, a critical issue that undermines the integrity of trust modelling in IoUT networks. The unique environmental and operational constraints of IoUT exacerbate the severity of this issue, making current detection methods insufficient. To address this issue, a recommendation evaluation method that leverages both filtering and weighting strategies is proposed to enhance the detection of dishonest recommendations. The model introduces a filtering technique that combines outlier detection with deviation analysis to make initial decisions based on both majority outcomes and personal experiences. Additionally, a belief function is developed to weight received recommendations based on multiple criteria, including freshness, similarity, trustworthiness, and the decay of trust over time. This multifaceted weighting strategy ensures that recommendations are evaluated from different perspectives to capture deceptive acts that exploit the complex nature of IoUT to the advantage of dishonest recommenders. To validate the proposed model, extensive comparative analyses with existing trust evaluation methods are conducted. Through a series of simulations, the efficacy of the model in capturing dishonest recommendation attacks and improving the accuracy rate of detecting more sophisticated attack scenarios is demonstrated. These results highlight the potential of the model to significantly enhance the trustworthiness of IoUT establishments.
... DTN operations are based on the abstract concept of message exchange, where messages are aggregated into "bundles" and processed by specific devices, such as "bundle forwarders" or DTN gateways. When reliable delivery of messages needs to be guaranteed, DTN gateways will send messages Stored in memory in a nonvolatile manner and map information between different transmissions through name resolution [20]. DTN gateways also perform authentication and access control on incoming traffic to ensure that they are allowed to forward; DTN architecture consists of regions and is composed of DTN gateways, in which regional DTN gateways are connected to each other and are responsible for the cross-regional forwarding of data packets, which is different from the working mechanism of ARPANET gateways [8]; In unstable or discontinuous connection environments, DTN moves messages by using specific time-related connections. ...
Delay tolerant network is a network architecture and protocol suite specifically designed to handle challenging communications environments, such as deep space communications, disaster response, and remote area communications. Although DTN [1]can provide efficient and reliable data transmission in environments with high latency, unstable connections, and high bit error rates, its energy consumption optimization problem is still a challenge, especially in scenarios with limited resources.To solve this problem, this study combines the Epidemic[2] and MaxProp[3] routing protocols with Machine Learning Models to optimize the energy consumption of DTNs. Hundreds of simulations were conducted in the ONE simulator, and an external real-world dataset from San Francisco taxi mobility traces [54] was imported. Random Forest[4] and Gradient Boosting Machine (GBM)[5] models were employed for data analysis. Through optimization involving Hyperparameter Tuning and Feature Selection, the Random Forest model achieved an R-squared value of 0.53, while the GBM model achieved an R-squared value of 0.65.
... Efficient and reliable data transmission from oceanic environments necessitates a robust water-to-air (W2A) communication system, a topic that has garnered significant interest in both academic and industrial fields [1]. The traditional strategy for W2A communication, which uses a floating buoy relay on the water surface, suffers from weak flexibility, poor confidentiality, and high overhead, limiting the scalability of the system [2]- [4]. ...
This work explores water-to-air optical wireless communication (W2A-OWC) transmission schemes and realizes a prototype of real-time W2A-OWC system based on field programmable gate array. This prototype comprises underwater nodes, aerial nodes, and transmitter-receiver hardware circuits. The real-time system employs multiple-input multiple-output technique and the low density parity check (LDPC) code of 5G-new radio for dynamic W2A-OWC. Additionally, the impact of background radiation is mitigated through spatial optical filtering. To validate the practical feasibility of the system, experiments are conducted in both indoor water tank and outdoor deep pool under strong background radiation. The frame error rate of the real-time system is tested under different LDPC code rates and transmitter-receiver configurations. The experimental results verify the feasibility of the realized W2A-OWC system.
... Here, the timing error of the IoUT target node clock obeys a zero-mean Gaussian variable with variance s 2 + 1 σ 2 . Taking into account the bias of the AUV positions, we introduce a new vector, λ = x f ,R , where x f = [x, y, s, o] denotes the unknown vector of target IoUT node,R = x (1) , · · · ,x (N K) denotes the set of AUV horizontal positions. Then, the joint PDF can be expressed as ...
In oceanographic and environmental monitoring, achieving precise localization and sensing through Integrated Sensing and Communication (ISAC) within the Internet of Underwater Things (IoUT) networks is paramount. However, ISAC-based IoUT systems present distinctive challenges, including depth-dependent propagation speed, asynchronous clock synchronization, and node mobility. This paper introduces an efficient asynchronous localization method explicitly tailored for ISAC-based IoUT networks, which effectively addresses both the stratification effect and node mobility. Our approach centers on an iterative least squares (LS) algorithm designed to localize Autonomous Underwater Vehicles (AUVs) while carefully considering propagation delay and location estimation. Furthermore, we introduce a mobility model grounded in target sensing mechanisms that rely on AUVs’ spatial coordinates and propulsion velocities, thereby enhancing the accuracy of target position estimation. We propose a novel precoding design for sensing using random acoustic signals within IoUT networks. To validate the effectiveness of our method, we conduct comprehensive Monte Carlo simulations and benchmark the results against state-of-the-art techniques. The findings demonstrate a significant reduction in estimation errors, confirming the superior efficiency of our approach compared to existing methods.
... In-depth exploration and study of oceans is of great importance to human development [1][2][3][4]. The concept of the Underwater Internet of Things (UIoT), which is defined as a world-wide network of smart interconnected underwater objects, has continued to gain in popularity since the 2010s [5]. The establishment of the UIoT and the realization of interconnection, information sharing, and cooperative operation between heterogeneous underwater intelligent devices are urgent global challenges. ...
The establishment of the Underwater Internet of Things (UIoT) and the realization of interconnection between heterogeneous underwater intelligent devices are urgent global challenges. Underwater acoustic networking is the most suitable technology to achieve UIoT for medium to long ranges. This paper presents an underwater Wi-Fi network, called uw-WiFi, that utilizes a master–slave mode architecture. uw-WiFi is dedicated to solving the problem of underwater acoustic networking with limited coverage range and number of nodes. To ensure the reliability of different types of data in the network, a reliable segmentation transmission protocol based on data type is designed. Additionally, on-demand scheduling based on the reservation MAC protocol is developed to solve the channel resource sharing problem. The uw-WiFi system has undergone shallow sea tests, and the experimental results demonstrate that the uw-WiFi network is capable of achieving a network throughput of 500 bps or higher, indicating superior network performance.
... Evaluation and findings: Evaluation of corals and their inhabitants [42], photo-mosaicking analysis and mapping of the seabed [43], object detection and categorization [44], plant identification [45], automatic fish [46], lobster [47], plankton [48] and other species recognition, as well as tracking and navigation [49] are a few examples of these. Monitoring and marine data management: Examples include environmental monitoring (such as water quality and pollution) [50], farming of fishes [51], monitoring and corrosion investigation of pipelines (such as in the oil and gas industry) [52], military surveillance [53], navigation support, marine forecast and warning systems (such as flood, red tide, tsunami) [54] and maritime geographic information systems [55]. ...
... Wireless underwater sensor networks (WUSNs) provide round-the-clock data collection at higher spatial and temporal resolutions than is possible via any other method 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]. ...
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-underwaterthings (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 enable wireless charging 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) 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 its own energy consumption. To the best of our knowledge, this is the first attempt at using RL for this application. 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.
... Recently, the advent of the Internet of Underwater Things (IoUT) as an emerging technology helps to connect UWSNs to the Internet so that it facilitates network administration to manage and monitor efficiently their UWSNs remotely (Domingo 2012). In IoUT, each sensor (i.e., underwater thing) senses a variety of phenomena such as pressure, temperature chemicals, etc. ...
During the last few years, the Internet of Underwater Things (IoUT) has become an interesting technology to discover unexplored underwater environments. IoUT enables scientists and researchers to remotely discover underwater phenomena and gather valuable information from the depths of the oceans using smart things. Due to the harshness of the underwater environment, collecting information with regard to QoS parameters and energy considerations is a major challenge. Software Defined Networking (SDN) is a centralized network management paradigm that helps to implement efficient routing approaches to provide QoS for network traffic flows. In this paper, we propose EQAFR as an energy-efficient routing schema by leveraging the capabilities of SDN to provide QoS for gathered underwater data which are sent from underwater things toward the sink. EQAFR is implemented in the SDN controller to gather the coordinate information and residual energy of things periodically. Then, it computes the delay and probability of data loss of the link and applies Fuzzy logic to compute the cost of links. Finally, it calculates optimal paths and installs the routes between the underwater things. Simulation results confirm that using EQAFR considerably improves QoS and prolongs the lifetime of underwater things.
... Network planning includes conventional UWSNs planned from Akyildiz et al. (3) and instantaneous UWSN planning in the shape of Internet of Underwater Things projected from Domingo (4). UWSNs include nodules that are employable on the exterior and under water. ...
Underwater wireless sensor networks (UWSNs) 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 Depthbased Routing) and CEEDBR (Cooperative Energy Efficient Depth-based Routing) procedures to improve network lifespan, energy efficacy, and amount
... 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.
This chapter explores the transformative intersection of Federated Learning (FL) and the Internet of Underwater Things (IoUT), presenting a paradigm shift in how underwater things operate autonomously and efficiently. The unique challenges posed by the underwater environment necessitate innovative solutions, and FL emerges as a promising approach to address data privacy, resource constraints, and decentralized learning. The chapter delves into the integration of FL techniques, discussing their applications, benefits, and challenges in the context of IoUT. This chapter aims to contribute to the evolving literature on underwater drone technologies, providing a comprehensive overview of how Federated Learning can empower the Internet of Underwater Things to operate intelligently, autonomously, and securely in challenging underwater environments.
Remotely operated vehicles (ROVs) enable underwater exploration and research but face imaging challenges from environmental conditions. This chapter examines how emerging technologies can enhance underwater imagery captured by ROVs. Specifically, the integration of artificial intelligence, machine learning (AI/ML), and Internet of Things (IoT) capabilities can automate and optimize image pre-processing, reduce noise, correct colors, and enable real-time analysis. Relevant algorithms and models are reviewed, including convolutional neural networks, color equalization, and utilization of RGB color proportions. This chapter begins by outlining the inherent environmental and technical challenges involved in capturing high-quality underwater images, particularly those obtained using remotely operated vehicles (ROVs). The discussion then shifts to the role of AI/ML in image pre-processing, with a specific focus on the models developed to improve image quality by reducing noise, adjusting color, and enhancing clarity. Various case studies are being carried out to examine the application of Internet of Things (IoT)-enabled sensors and cameras that are installed on remotely operated vehicles (ROVs), along with automated image pre-processing and real-time data transmission. This study showcases the practicality of these technologies in marine biology, underwater exploration, and environmental monitoring through a diverse range of illustrations. Furthermore, the chapter highlights the importance of maintaining a harmonious equilibrium between environmental and ethical factors when utilizing state-of-the-art underwater technology. This chapter concludes by presenting a perspective on future advancements and proposing recommendations for the optimal incorporation of AI/ML and the Internet of Things into ROV technology.
The underwater Internet of Things (UIoT) and remote sensing are significant for biodiversity preservation, environmental protection, national security, disaster assistance, and technological innovation. Assigning tasks to autonomous underwater vehicles (AUVs) is a fundamental challenge in underwater technology and exploration. Remote sensing and AUVs are vital for pollution detection, disaster prevention, marine observation, and ocean monitoring. This work presents an optimized network connectivity using a multi-attribute decision-making approach for underwater IoT deployment. A feature engineering approach highlights the significant characteristics of underwater things, incorporating remote sensing data, and a multi-objective optimization method is used to select optimal UIoT for effective task allocation in deep-sea environments. A balance between data transmission, energy economy, and operational performance is necessary for efficient task distribution. Effective communication algorithms and protocols are needed to maintain environmental sustainability, protect marine ecosystems, and improve underwater monitoring enhanced by remote sensing technologies. Multi-criteria decision-making (MCDM) is beneficial for addressing various challenges in underwater technology, considering factors such as mission objectives, energy efficiency, environmental conditions, vehicle performance, safety, and much more. The proposed criteria importance through intercriteria correlation (CRITIC) methodology will assess technical competencies like communication, resilience, navigation, and safety in an underwater environment, leveraging remote sensing and aiding decision-makers in selecting appropriate undersea devices and vehicles for enhancing communication and transportation. This method prioritizes characteristics and aligns them with specific objectives, improving decision-making quality in the marine environment.
Underwater wireless sensor networks (UWSNs) have emerged as a potent solution for oceanographic data collection, underwater exploration, and monitoring of underwater ecosystems. However, the unique and harsh underwater environment, such as limited bandwidth, high propagation delay, and significant energy constraints, creates myriad challenges in designing energy-efficient communication protocols. This research explores developing and implementing innovative energy-efficient protocols tailored for UWSNs to enhance their longevity and reliability. The authors introduce a novel protocol that employs a hybrid of clustering and routing algorithms to minimize energy consumption and enhance network longevity. The protocol is designed to tackle energy consumption, data transmission reliability, and network scalability issues. The findings from the implementation in a simulated underwater environment demonstrate notable improvements in energy conservation and network lifespan, thereby affirming the potential applicability of the proposed protocols in real-world underwater applications.
Marine in-situ data is collected by sensors mounted on fixed or mobile systems deployed into the ocean. This type of data is crucial both for the ocean industries and public authorities, e.g., for monitoring and forecasting the state of marine ecosystems and/or climate changes. Various public organizations have collected, managed, and openly shared in-situ marine data in the past decade. Recently, initiatives like the Ocean Decade Corporate Data Group have incentivized the sharing of marine data of public interest from private companies aiding in ocean management. However, there is no clear understanding of the impact of data quality in the engineering of systems, as well as on how to manage and exploit the collected data. In this paper, we propose main architectural decisions and a data flow-oriented component and connector view for marine in-situ data streams. Our results are based on a longitudinal empirical software engineering process, and driven by knowledge extracted from the experts in the marine domain from public and private organizations, and challenges identified in the literature. The proposed software architecture is instantiated and exemplified in a prototype implementation.
With advent of Internet of Things (IoT) an exponential growth has been observed in recent times towards the use of fifth generation (5G) network to share data among anything and even everything around connected in billions. The exchange of large amount of data by these devices or objects accumulates network overhead in the IoT infrastructure in terms of energy, routing, battery charge, data rate, packet delivery/loss rate, availability, interoperability, congestion, scalability, cost and security. Hence it is highly essential to project optimal solutions to uphold thereby the quality of service (QoS) in available network. This study provides a thorough literature survey of diverse optimization techniques in IoT aided wireless networks like Mobile Ad-hoc NETwork (MANET) driven Internet of Mobile Things (IoMobT), Vehicular Ad-hoc NETwork (VANET) driven Internet of Vehicles (IoV), Flying Ad-hoc NETwork (FANET) driven Internet of Flying Things (IoF), Robot Ad-hoc NETwork (RANET) enabled Internet of Robots (IoR), Ship Ad-hoc NETwork (SANET) driven Internet of Ships (IoS) and Underwater or Underground Ad-hoc NETwork (UANET) in Internet of Underwater or Underground Things (IoU). It categorizes papers based on the issues resolved by the examined works and optimization strategies employed and then it contrasts and condenses the salient characteristics of each kind of publication. It also even sketches a preview of IoT along with its evolving trends and cutting-edge-solutions for improving QoS. Our survey attempts to give readers a better grasp of the principles behind various computing models and to examine QoS network optimization strategies across a range of IoT models.
We describe a biomimicking interception scheme tailored to Underwater Acoustic Communications (UAC), which aims at separating authentic and biomimicking signals. Our interceptor leverages the expected stability of the biomimicking sources, as opposed to vocalizations by marine fauna, which are expected to move fast and rapidly change orientation. Consequently, the channel impulse response (CIR) of the link between a receiver and a biomimicking source is expected to be much more stable than those corresponding to actual vocalizations. We quantify this stability by testing the randomness of the representation of the CIRs. The latter are represented by two similarity metrics: the cross-correlation and the sample entropy between adjacent CIRs features. We offered two interception measures: 1) testing the similarity between a Gaussian distribution and the distribution of the similarity measures using the Kullback–Leibler divergence (KLD) criteria for quantification, and 2) the minimum number of clusters to effectively segment the similarity measures as a point cloud. Results from simulations for artificial signals mimicking dolphin whistles and the outcomes of a lake trial demonstrate the effectiveness of our biomimicking interceptor.
Organic photovoltaic (OPV) technology holds tremendous promise as a sustainable power source for underwater off‐grid systems. However, research on underwater OPV cells is relatively scarce. Here, this gap is addressed by focusing on the exploration and development of OPV cells specifically designed for underwater applications. An acceptor, named ITO‐4Cl, with excellent water resistance, is rationally designed and synthesized. Benefiting from its low energetic disorder and an absorption spectrum well‐suited to the underwater environment, the ITO‐4Cl‐based OPV cell achieves an unprecedented power conversion efficiency (PCE) of over 25.6% at a water depth of 1 m. Additionally, under 660 nm laser irradiation, the cell demonstrates a notable PCE of 31.6%, indicating its potential for underwater wireless energy transfer. Due to the mitigation of thermal effects from solar irradiation, the lifetime of the ITO‐4Cl‐based OPV cell exceeds 7000 h. Additionally, a flexible OPV cell is fabricated that maintains its initial PCE even under exposure to high pressures of 5 MPa. A 32.5 cm² flexible module achieves an excellent PCE of 17%. This work fosters a deeper understanding of underwater OPV cells and highlights the promising prospects of OPV cells for underwater applications.
This paper considers an underwater wireless sensor network where a sink station collects time-sensitive information from multiple sensors. For timely monitoring, the sink station aims to maximize the data freshness of the entire network. The difficulty includes time-varying channel states, limited transmission bandwidth and power consumption caused by underwater acoustic communication. Moreover, due to the time-varying service requirements, the importance of data is unknown until it is received and processed by the sink station. To overcome these difficulties, we characterize the data freshness at the terminal through a set of non-decreasing functions with respect to the popular metric Age of Information (AoI). To save the energy consumption, each sensor will transmit with different power to combat the different channel states. Then, we relax the bandwidth constraint and resort to the online learning framework with Lyapunov drift analysis to design a jointly scheduling and power control algorithm based on historical observations. The algorithm is proven to achieve the sub-linear expected performance for both cumulative age regret and bandwidth violation. Finally, we propose the truncated scheduling strategy to satisfy the hard bandwidth constraint. Simulation results validate the performance of the proposed algorithms compared with the optimal offline algorithm with complete information.
In this study, a novel SnO 2 –Zr–F nanostructured composite was successfully synthesized through a mild chemical reaction. The crystalline nature of the composite was characterized using XRD, revealing an average crystalline size of 28.31 nm. FE-SEM images illustrated an agglomerated spherical morphology with appropriate elemental ratios. The optical properties of the nanocomposite are identified by UV–vis spectroscopy with Tauc plot, and the calculated bandgap is 2 eV. Photocatalytic activity was assessed against cationic (Rhodamine B) and anionic (Eosin yellow) dyes under sunlight for 150 min, resulting in a maximum degradation efficiency of 92 % and 98 %, respectively. Furthermore, the antibacterial performance of the composite was evaluated against S. aureus and E. coli bacteria. The findings suggest that the prepared nanocomposite exhibits promising potential for environmental applications, showcasing its efficacy in both photocatalytic and antibacterial domains.
To cope with the extremely double-dispersive channels in underwater acoustic (UWA) communication, orthogonal time frequency space (OTFS) modulation has been regarded as a potential candidate since delay-Doppler symbols can fully utilize the time-frequency diversity. So far, limited work has been devoted to UWA-OTFS systems, and the Doppler squint effect (DSE) in UWA channels is always ignored in these researches, which causes severe performance degradation and even transmission failure. Though the DSE-aware modeling has been investigated for OTFS-based mobile communications in our prior work, the assumption of system constraints cannot be satisfied in UWA-OTFS scenarios due to the significantly smaller velocity of sound, which forces us to reconsider the input-output evaluation and the corresponding system design. In this paper, UWA-OTFS systems are carefully investigated considering DSE. The intuitive characterization of the inputoutput relation for ideal waveforms is derived at first, where we also offer the design principle of system parameters. The precise closed-form representation with practical waveforms is then provided as the guideline for realistic UWA-OTFS systems. Based on the establishment of the input-output analysis, the linear minimum mean squared error (LMMSE) successive interference cancellation (SIC) detector is applied to carry out the equalization and data recovery iteratively. Simulation results demonstrate the significance of considering DSE in UWA-OTFS systems and the excellent performance of our proposed detection scheme
The term “Internet of Underwater Things (IoUT)” refers to a network of intelligent interconnected underwater devices designed to monitor various underwater activities. The IoUT allows for a network of autonomous underwater vehicles (AUVs) to communicate with each other, sense their surroundings, collect data, and transmit them to control centers on the surface at typical Internet speeds. These data serve as a valuable resource for various tasks, including conducting crash surveys, discovering shipwrecks, detecting early signs of tsunamis, monitoring animal health, obtaining real-time aquatic information, and conducting archaeological expeditions. This paper introduces an additional set of alternative simulation tools for underwater networks. We categorize these tools into open-source and licensed simulator options and recommend that students consider using open-source simulators for monitoring underwater networks. There has not been widespread deployment or extensive research on underwater 5G-based networks. However, simulation tools provide some general insights into the challenges and potential issues associated with evaluating such networks, based on the characteristics of underwater communication and 5G, by surveying 5G-based underwater networks and 5G key aspects addressed by the research community in underwater network systems. Through an extensive review of the literature, we discuss the architecture of both Internet of Underwater application-assisted AUVs and Internet of Underwater Things communications in the 5G-based system.
Underwater wireless optical communication is the best alternative for many applications especially for high bandwidth data communication between underwater objects and vehicles. The implementation of coding scheme along with advanced modulation technique and equalisation methods is identified as a key research scope for enhancing the performance of the system. In this paper, the coded generalised frequency division multiplexing (GFDM) technology is employed to provide high-data rates and less out-of-band emission. The Bose-Chaudhuri-Hocquenghem (BCH) and Reed-Solomon (RS) coding schemes along with equalisation techniques namely normalised least mean square (NLMS)-based decision feedback equalisers (DFE), minimum mean square error (MMSE) and zero forcing (ZF) are utilized to reduce inter symbol interference (ISI). The bit error rate (BER) performance is evaluated in the presence of pointing error (PE) and turbulence using Monte Carlo channel modelling simulations. The results showed that RS coding with NLMS-DFE outperforms other techniques and achieves a BER of roughly 10 −5 with a signal-to-noise ratio levels below 20 dB. The simulation results demonstrate that RS code with 15 total symbols per code word and 3 data symbols, i.e., RS (15, 3) and BCH code with 31 total symbols in a code word and 6 data symbols, i.e., BCH (31, 6) provided the best error performance among other coding schemes employed. It is inferred that RS (15, 3) coded 2 × 2 multiple input multiple output systems with NLMS-DFE achieved a BER value of 1.1925 × 10 −5 at 11 dB which is 16 dB less than uncoded system. Thus, the coded GFDM improves overall BER performance and has the potential to provide higher reliability for internet of underwater things (IoUT) applications.
The automatic modulation classification for surface and underwater sensors in the perception layer is crucial in the Internet of Underwater Things (IoUT), where Deep Learning (DL) is becoming an important tool to improve classification accuracy. This work focuses on the radio environment in the perception layer. The biggest challenge in popular DL-based methods is deploying the algorithm in edge devices with limited computing power. Network pruning has been found to be a critical and effective method for network lightweight and the improvement of resources, thus mitigating potential interference. While not studied in previous work, this paper fills the hole in algorithm deployment’s criterion selection and accuracy loss. Specifically, we develop a Convolutional Neural Network (CNN) based lightweight framework on distinguishing modulated signals from generated datasets (which is named DLocean) in different Signal-to-Noise Ratios (SNR). The performance of the lightweight framework is tested on the edge device. The experiments demonstrate that the proposed model compensates for accuracy and can successfully classify the modulation schemes with 93.4% accuracy at the SNR=5 dB. Our results also show that the proposed framework can improve performance without exceeding the original network complexity on edge device deployment.
This paper investigates the application of self-organizing networks in solving the interference problem in underwater acoustic communication networks (UACNs) with the coexistence of multi-node. In this network, each node autonomously adjusts its power based on locally observed information without central controller intervention. Considering the non-convexity of the optimization problem with quality-of-service constraints and the dynamic nature of the underwater environment, we propose a reinforcement learning (RL)-based approach coupled with a distributed coordination mechanism, namely the multi-agent-based transfer Dyna-Q algorithm (MA-TDQ). This algorithm combines Q-learning with Dyna structure and transfer learning, and can quickly obtain optimal intelligent resource management strategies. Furthermore, we rigorously demonstrate the convergence of the MA-TDQ algorithm to Nash equilibrium. Simulation results indicate that the proposed distributed coordination learning algorithm outperforms other existing learning algorithms in terms of learning efficiency, network transmission rate, and communication service quality.
The Internet of Underwater Things (IoUT) relies on wireless communication devices that are arranged in an open underwater environment and can interact with other devices through acoustic communication technology. However, due to their limited resources and open underwater environment, IoUT has been suffering from a high risk of malware attacks. As the two main parts of IoUT, autonomous underwater vehicles (AUVs) and underwater wireless rechargeable sensor networks (UWRSNs) are more favored by attackers and can be directly attacked by malware, which can lead to the cross-propagation of malware when AUVs and UWRSNs exchange information. To mitigate that threat, there is an urgent need to study the propagation patterns of malware and control their spread. Therefore, we establish a mathematical model based on the fractional-order theoretical framework to investigate the malware propagation patterns in two coupled networks (UWRSNs and AUVs). Then, we combine immune, charging and quarantine delays in control and derive the optimal control strategies based on optimal control theory. Moreover, to improve the generality of control, we propose a machine learning (ML) controller that combines machine learning (e.g., deep neural network (DNN) and random forest (RF)) with control theory. Ultimately, our simulation experiments show that the proposed optimal control strategy is more effective in inhibiting the spread of malware while obtaining the minimum control cost under different fractional-order scenes. At the same time, the ML-based control results are close to the optimal control.
This article studies the distributed power management problem in underwater acoustic communication networks (UACNs) with the coexistence of multiple transmitter–receiver pairs, where each transmitter selects its transmit power based only on local observations without the involvement of any central controller. This article aims to maximize the network transmission rate based on maintaining Nash equilibrium (NE) among multiple transmitter–receiver pairs. We model the selfish behavior of each emitter as a noncooperative game. In this game, on the one hand, the distance between the transmitter and the receiver is introduced as an interference weight factor to modify the effective interference model; on the other hand, the utility function of the game is constructed by combining the information transmission rate of the transmitter and its remaining energy. Moreover, it is successfully proved that the utility function has an NE solution. Subsequently, a multiagent dual
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network algorithm (MA-DDQN-PR) based on priority replay is proposed to achieve the optimal transmission strategy in dynamically changing channel and interference environments. Each transmitter in this algorithm acts as an agent, interacting with the communication environment and receiving different observations. But at the same time, they have a common reward function and centrally train the
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network by summarizing the actions of other agents, thereby improving the power control selected by each agent. Finally, simulation results show that the proposed algorithm outperforms other existing learning algorithms in terms of network transmission rate, network energy efficiency, and transmitter lifetime.
Data hiding has become a hot research topic in recent years due to increased attention placed on the copyright protection of ocean images and related digital records. Further, high image volumes put enormous pressure on transmission bandwidth and storage capabilities. This paper proposes an innovative deep learning‐based data‐hiding technique for ocean images. First, a down‐sampling scheme is applied to compress the secret mark before embedding it in the host media. Then, a convolutional neural network is used to embed and recover compressed marks into or from the host ocean image. Finally, a generative adversarial network‐based reconstruction network is used to reconstruct the high‐quality mark image. Our experiments show that the proposed work not only maintains high imperceptibility and robustness against many attacks but also provides better data‐hiding performance than related works.
The majority of the Earth’s surface is covered by water, with oceans holding approximately 97% of this water and serving as the lifeblood of our planet. These oceans are essential for various purposes, including transportation, sustenance, and communication. However, establishing effective communication networks between the numerous sub-islands present in many parts of the world poses significant challenges. Underwater optical wireless communication, or UWOC, can indeed be an excellent solution to provide seamless connectivity underwater. UWOC holds immense significance due to its ability to transmit data at high rates, low latency, and enhanced security. In this work, we propose polarization division multiplexing-based UWOC system under the impact of salinity with an on–off keying (OOK) modulation format. The proposed system aims to establish high-speed network connectivity between underwater divers/submarines in oceans at different salinity levels. The numerical simulation results demonstrate the effectiveness of our proposed system with a 2 Gbps data rate up to 10.5 m range in freshwater and up to 1.8 m in oceanic waters with salinity up to 35 ppt. Successful transmission of high-speed data is reported in underwater optical wireless communication, especially where salinity impact is higher.
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.
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 in order to achieve different performance requirements. We demonstrate through simulations that our protocol can satisfy different application requirements and achieve a good trade-off among delivery ratio, end-to-end delay and energy consumption.
This paper describes an intelligent underwater acoustic system
that allows the positions of several divers to be tracked in
three-dimensional space and to telemeter each diver's co-ordinates to a
remote receiver at the surface. The positions of the divers are fixed
using three randomly deployed seabed transponders that may be described
as `intelligent'. The transponders fix their own relative positions and
the position of the surface receiver, usually a vessel, by an exchange
of coded acoustic pulses. These positions can be related to a
differential GPS system at the surface if absolute co-ordinates are
required. The divers each know their own position from a wrist-worn
computer with a backlit graphical/numerical display. As well as the
current position, the display can show the track from the beginning of
the dive, the location of the surface vessel and the instantaneous
position of the other divers. Also, a transponder can be attached to
remotely operated vehicle (ROV) or autonomous underwater vehicle (AUV)
to allow the position and data of the vehicle to be tracked by the
surface vessel and by any divers in the vicinity
We review the rationale behind the current design of the Delay/Disruption Tolerant Networking (DTN) Architecture and highlight some remaining open issues. Its evolution, from a focus on deep space to a broader class of heterogeneous networks that may suffer disruptions, affected design decisions spanning naming and addressing, message formats, data encoding methods, routing, congestion management and security. Having now achieved relative stability with the design, additional experience is required in long-running operational environments in order to fine tune our understanding of DTN concepts and the types of capabilities that are worth the investment in implementation complexity. We expect key management, handling of congestion, multicasting capability, and routing to remain active areas of research and development, and that DTN may continue to be an active research endeavor for at least the next few years.
The Energy Harvesting Eel (Eel) is a new device that uses
piezoelectric polymers to convert the mechanical flow energy, available
in oceans and rivers, to electrical power. Eel generators make use of
the regular trail of traveling vortices behind a bluff body to strain
the piezoelectric elements; the resulting undulating motion resembles
that of a natural eel swimming. Internal batteries are used to store the
surplus energy generated by the Eel for later use by a small, unattended
sensor or robot. Because o