158 research outputs found

    Advances in integrating autonomy with acoustic communications for intelligent networks of marine robots

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    Submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy at the Massachusetts Institute of Technology and the Woods Hole Oceanographic Institution February 2013Autonomous marine vehicles are increasingly used in clusters for an array of oceanographic tasks. The effectiveness of this collaboration is often limited by communications: throughput, latency, and ease of reconfiguration. This thesis argues that improved communication on intelligent marine robotic agents can be gained from acting on knowledge gained by improved awareness of the physical acoustic link and higher network layers by the AUV’s decision making software. This thesis presents a modular acoustic networking framework, realized through a C++ library called goby-acomms, to provide collaborating underwater vehicles with an efficient short-range single-hop network. goby-acomms is comprised of four components that provide: 1) losslessly compressed encoding of short messages; 2) a set of message queues that dynamically prioritize messages based both on overall importance and time sensitivity; 3) Time Division Multiple Access (TDMA) Medium Access Control (MAC) with automatic discovery; and 4) an abstract acoustic modem driver. Building on this networking framework, two approaches that use the vehicle’s “intelligence” to improve communications are presented. The first is a “non-disruptive” approach which is a novel technique for using state observers in conjunction with an entropy source encoder to enable highly compressed telemetry of autonomous underwater vehicle (AUV) position vectors. This system was analyzed on experimental data and implemented on a fielded vehicle. Using an adaptive probability distribution in combination with either of two state observer models, greater than 90% compression, relative to a 32-bit integer baseline, was achieved. The second approach is “disruptive,” as it changes the vehicle’s course to effect an improvement in the communications channel. A hybrid data- and model-based autonomous environmental adaptation framework is presented which allows autonomous underwater vehicles (AUVs) with acoustic sensors to follow a path which optimizes their ability to maintain connectivity with an acoustic contact for optimal sensing or communication.I wish to acknowledge the sponsors of this research for their generous support of my tuition, stipend, and research: the WHOI/MIT Joint Program, the MIT Presidential Fellowship, the Office of Naval Research (ONR) # N00014-08-1-0011, # N00014-08-1-0013, and the ONR PlusNet Program Graduate Fellowship, the Defense Advanced Research Projects Agency (DARPA) (Deep Sea Operations: Applied Physical Sciences (APS) Award # APS 11-15 3352-006, APS 11-15-3352-215 ST 2.6 and 2.7

    Implementation of an underwater acoustic modem with network capability

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    This paper introduces the underwater acoustic modem as implemented within the UAN – Underwater Acoustic Network project. The low power modem has implemented turbo equalization algorithms in addition to variable spread rate direct sequence spread spectrum signaling. The network layer implemented on the modem support automatic network discovery, multi hop routing and support for mobile nodes, and when expanded with a single board computer via serial line it supports IP connectivity end-to-end. Experimental results from sea trials are presented

    A discovery process for initializing ad hoc underwater acoustic networks

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    Seaweb is an underwater acoustic wide-area network connecting autonomous, distributed nodes. Prior iterations of Seaweb relied on operator intervention to initialize and manually configure the network routes. This thesis implements a network discovery process that enables a field of spontaneously deployed, ad hoc nodes to auto-configure for networking purposes. Network routing is initialized as nodes in the network are discovered, with routes chosen according to comparative evaluation of a cost function for all candidate routes. The implemented network discovery process is tested using computer simulation and sea trial data. The resultant network routes obtained upon completion of the ad hoc network discovery process are compared with those derived from Dijkstra's algorithm. It is concluded that the network discovery process always produces a shortest-path route from a master node to any other discovered nodes in the network. Sensitivity studies on the route cost evaluation function are performed, and an alternative network discovery scheme is discussed.http://archive.org/details/adiscoveryproces109453774Republic of Singapore Navy author.Approved for public release; distribution is unlimited

    IoT Transmission Technologies for Distributed Measurement Systems in Critical Environments

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    Distributed measurement systems are spread in the most diverse application scenarios, and Internet of Things (IoT) transmission equipment is usually the enabling technologies for such measurement systems that need to feature wireless connectivity to ensure pervasiveness. Because wireless measurement systems have been deployed for the last years even in critical environments, assessing transmission technologies performances in such contexts is fundamental. Indeed, they are the most challenging ones for wireless data transmission due to their intrinsic attenuation capabilities. Several scenarios in which measurement systems can be deployed are analysed. Firstly, marine contexts are treated by considering above-the-sea wireless links. Such setting can be experienced in whichever application requiring remote monitoring of facilities and assets that are offshore installed. Some instances are offshore sea farming plants, or remote video monitoring systems installed on seamark buoys. Secondly, wireless communications taking place from the underground to the aboveground are covered. This scenario is typical of precision agriculture applications, where the accurate measurement of underground physical parameters is needed to be remotely sent to optimise crops reducing the wastefulness of fundamental resources (e.g., irrigation water). Thirdly, wireless communications occurring from the underwater to the abovewater are addressed. Such situation is inevitable for all those infrastructures monitoring conservation status of underwater species like algae, seaweeds and reef. Then, wireless links happening traversing metal surfaces and structures are tackled. Such context is commonly encountered in asset tracking and monitoring (e.g., containers), or in smart metering applications (e.g., utility meters). Lastly, sundry harsh environments that are typical of industrial monitoring (e.g., vibrating machineries, harsh temperature and humidity rooms, corrosive atmospheres) are tested to validate pervasive measurement infrastructures even in such contexts that are usually experienced in Industrial Internet of Things (IIoT) applications. The performances of wireless measurement systems in such scenarios are tested by sorting out ad-hoc measurement campaigns. Finally, IoT measurement infrastructures respectively deployed in above-the-sea and underground-to-aboveground settings are described to provide real applications in which such facilities can be effectively installed. Nonetheless, the aforementioned application scenarios are only some amid their sundry variety. Indeed, nowadays distributed pervasive measurement systems have to be thought in a broad way, resulting in countless instances: predictive maintenance, smart healthcare, smart cities, industrial monitoring, or smart agriculture, etc. This Thesis aims at showing distributed measurement systems in critical environments to set up pervasive monitoring infrastructures that are enabled by IoT transmission technologies. At first, they are presented, and then the harsh environments are introduced, along with the relative theoretical analysis modelling path loss in such conditions. It must be underlined that this Thesis aims neither at finding better path loss models with respect to the existing ones, nor at improving them. Indeed, path loss models are exploited as they are, in order to derive estimates of losses to understand the effectiveness of the deployed infrastructure. In fact, some transmission tests in those contexts are described, along with providing examples of these types of applications in the field, showing the measurement infrastructures and the relative critical environments serving as deployment sites. The scientific relevance of this Thesis is evident since, at the moment, the literature lacks a comparative study like this, showing both transmission performances in critical environments, and the deployment of real IoT distributed wireless measurement systems in such contexts

    Algorithms for propagation-aware underwater ranging and localization

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    Mención Internacional en el título de doctorWhile oceans occupy most of our planet, their exploration and conservation are one of the crucial research problems of modern time. Underwater localization stands among the key issues on the way to the proper inspection and monitoring of this significant part of our world. In this thesis, we investigate and tackle different challenges related to underwater ranging and localization. In particular, we focus on algorithms that consider underwater acoustic channel properties. This group of algorithms utilizes additional information about the environment and its impact on acoustic signal propagation, in order to improve the accuracy of location estimates, or to achieve a reduced complexity, or a reduced amount of resources (e.g., anchor nodes) compared to traditional algorithms. First, we tackle the problem of passive range estimation using the differences in the times of arrival of multipath replicas of a transmitted acoustic signal. This is a costand energy- effective algorithm that can be used for the localization of autonomous underwater vehicles (AUVs), and utilizes information about signal propagation. We study the accuracy of this method in the simplified case of constant sound speed profile (SSP) and compare it to a more realistic case with various non-constant SSP. We also propose an auxiliary quantity called effective sound speed. This quantity, when modeling acoustic propagation via ray models, takes into account the difference between rectilinear and non-rectilinear sound ray paths. According to our evaluation, this offers improved range estimation results with respect to standard algorithms that consider the actual value of the speed of sound. We then propose an algorithm suitable for the non-invasive tracking of AUVs or vocalizing marine animals, using only a single receiver. This algorithm evaluates the underwater acoustic channel impulse response differences induced by a diverse sea bottom profile, and proposes a computationally- and energy-efficient solution for passive localization. Finally, we propose another algorithm to solve the issue of 3D acoustic localization and tracking of marine fauna. To reach the expected degree of accuracy, more sensors are often required than are available in typical commercial off-the-shelf (COTS) phased arrays found, e.g., in ultra short baseline (USBL) systems. Direct combination of multiple COTS arrays may be constrained by array body elements, and lead to breaking the optimal array element spacing, or the desired array layout. Thus, the application of state-of-the-art direction of arrival (DoA) estimation algorithms may not be possible. We propose a solution for passive 3D localization and tracking using a wideband acoustic array of arbitrary shape, and validate the algorithm in multiple experiments, involving both active and passive targets.Part of the research in this thesis has been supported by the EU H2020 program under project SYMBIOSIS (G.A. no. 773753).This work has been supported by IMDEA Networks InstitutePrograma de Doctorado en Ingeniería Telemática por la Universidad Carlos III de MadridPresidente: Paul Daniel Mitchell.- Secretario: Antonio Fernández Anta.- Vocal: Santiago Zazo Bell

    Energy harvesting for marine based sensors

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    This work examines powering marine based sensors (MBSs) by harvesting energy from their local environment. MBSs intrinsically operate in remote locations, traditionally requiring expensive maintenance expeditions for battery replacement and data download. Nowadays, modern wireless communication allows real-time data access, but adds a significant energy drain, necessitating frequent battery replacement. Harvesting renewable energy to recharge the MBSs battery, introduces the possibility of autonomous MBS operation, reducing maintenance costs and increasing their applicability. The thesis seeks to answer if an unobtrusive energy harvesting device can be incorporated into the MBS deployment to generate 1 Watt of average power. Two candidate renewable energy resources are identified for investigation, ocean waves and the thermal gradient across the air/water interface. Wave energy conversion has drawn considerable research in recent years, due to the large consistent energy flux of ocean waves compared to other conventional energy sources such as solar or wind, but focussing on large scale systems permanently deployed at sites targeted for their favourable wave climates. Although a small amount of research exists on using wave energy for distributed power generation, the device sizes and power outputs of these systems are still one to two orders of magnitude larger than that targeted in this thesis. The present work aims for an unobtrusive device that is easily deployable/retrievable with a mass less than 50kg and which can function at any deployment location regardless of the local wave climate. Additionally, this research differs from previous work, by also seeking to minimise the wave induced pitch motion of the MBS buoy, which negatively affects the data transmission of the MBS due to tilting and misalignment of the RF antenna. Thermal energy harvesting has previously been investigated for terrestrial based sensors, utilising the temperature difference between the soil and ambient air. In this thesis, the temperature difference between the water and ambient air is utilised, to present the first investigation of this thermal energy harvesting concept in the marine environment. A prototype wave energy converter (WEC) was proposed, consisting of a heaving cylindrical buoy with an internal permanent magnet linear generator. A mathematical model of the prototype WEC is derived by coupling a hydrodynamic model for the motion of the buoy with a vibration energy harvester model for the generator. The wave energy resource is assessed, using established mathematical descriptions of ocean wave spectra and by analysing measured wave data from the coast of Queensland, resulting in characteristic wave spectra that are input to the mathematical model of the WEC. The parameters of the WEC system are optimised, to maximise the power output while minimising the pitch motion. A prototype thermal energy harvesting device is proposed, consisting of a thermoelectric device sandwiched between airside and waterside heat exchangers. A mathematical model is derived to assess the power output of the thermal energy harvester using different environmental datasets as input. A physical prototype is built and a number of experiments performed to assess its performance. The results indicate that the prototype WEC should target the high frequency tail of ocean wave spectra, diverging from traditional philosophy of larger scale WECs which target the peak frequency of the input wave spectrum. The analysis showed that the prototype WEC was unable to provide the required power output whilst remaining below 100kg and obeying a 40 degrees pitch angle constraint to ensure robust data transmission. However, a proposed modification to the WECs cylindrical geometry, to improve its hydrodynamic coupling to the input waves, was shown to enable the WEC to provide the required 1W output power whilst obeying the pitch constraints and having a mass below 50kg. The thermal energy harvester results reveal that the thermal gradient across the air/water interface alone is not a suitable energy resource, requiring a device with a cross-sectional area in excess of 100m² to power a MBS. However, including a solar thermal energy collector to increase the airside temperature, greatly improves the performance and enables a thermal energy harvester with a cross-sectional area on the order of 1m² to provide 1W of output power. The findings in this thesis suggest that a well hydrodynamically designed buoy can provide two major benefits for a MBS deployment: enabling efficient wave energy absorption by the MBS buoy, and minimising the wave induced pitch motion which negatively affects the data transmission

    Smart marine sensing systems for integrated multi-trophic aquaculture (IMTA)

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    Aquaculture farming faces challenges to increase production whilst maintaining sustainability by reducing environmental impact and ensuring efficient resource usage. One solution is to use an Integrated Multi-Trophic Aquaculture (IMTA) approach, where a variety of different species are grown in the same site, taking advantage of by-products (such as waste and uneaten food) from one species as inputs (fertilizer, food, and energy) for the growth of other species. However, the remote monitoring of environmental and biological conditions is crucial to understand how the species interact with each other and with the environment, and to optimise the IMTA production and management system. Environmental monitoring of aquatic environments is already well supplied by commercial off-the-shelf sensors, but these sensors often measure only one parameter, which increases the power consumption and cost when monitoring multiple environmental variables with a fine-scale resolution. Current monitoring solutions for seaweed and kelp also include satellite and aerial sensing, which cover large areas effectively. However, these methods do not offer high-resolution, specific local data for growing sites, and are usually limited by turbidity and weather conditions. Another limitation of available commercial systems is data recovery. Most of them require that the sensor be retrieved to download data directly, increasing cost of maintenance. Radio Frequency Identification (RFID) systems that transmit in the near field (Near Field Communication – NFC) are less attenuated by the seawater environment than higher-frequency communications, and thus potentially provide a more viable alternative for underwater data transmission. In this work, we present a novel miniature low-power multi-sensor modality NFC-enabled data acquisition system to monitor a variety of farmed aquaculture species. This sensor system monitors temperature, light intensity, depth, and motion, logging the data collected internally. The sensor device can communicate with NFC-enabled readers (such as smartphones) to configure the sensors with custom sampling frequencies, communicate status, and to download data. It also has an internal machine learning enabled microcontroller, which can be used to perform data analysis internally. The device is designed to be attachable to seaweed and kelp blades or stipes. The system designed was tested in lab to characterise its sensors and to determine its battery lifetime. The sensor device was then deployed in an IMTA farm in Bertraghboy Bay, Connemara, Ireland, with the help of the Marine Institute. The data collected from the device was then correlated with environmental sensors placed in the site. Future work involves incorporating data analytics and machine learning algorithms to process data internally, allowing for lower transmission requirements

    Multicarrier communication over underwater acoustic channels with nonuniform Doppler shifts

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    Author Posting. © IEEE, 2008. This article is posted here by permission of IEEE for personal use, not for redistribution. The definitive version was published in IEEE Journal of Oceanic Engineering 33 (2008): 198-209, doi:10.1109/JOE.2008.920471.Underwater acoustic (UWA) channels are wideband in nature due to the small ratio of the carrier frequency to the signal bandwidth, which introduces frequency-dependent Doppler shifts. In this paper, we treat the channel as having a common Doppler scaling factor on all propagation paths, and propose a two-step approach to mitigating the Doppler effect: 1) nonuniform Doppler compensation via resampling that converts a "wideband" problem into a "narrowband" problem and 2) high-resolution uniform compensation of the residual Doppler. We focus on zero-padded orthogonal frequency-division multiplexing (OFDM) to minimize the transmission power. Null subcarriers are used to facilitate Doppler compensation, and pilot subcarriers are used for channel estimation. The receiver is based on block-by-block processing, and does not rely on channel dependence across OFDM blocks; thus, it is suitable for fast-varying UWA channels. The data from two shallow-water experiments near Woods Hole, MA, are used to demonstrate the receiver performance. Excellent performance results are obtained even when the transmitter and the receiver are moving at a relative speed of up to 10 kn, at which the Doppler shifts are greater than the OFDM subcarrier spacing. These results suggest that OFDM is a viable option for high-rate communications over wideband UWA channels with nonuniform Doppler shifts.B. Li and S. Zhou are supported by the ONR YIP grant N00014-07-1-0805 and the NSF grant ECCS-0725562. M. Stojanovic is supported by the ONR grant N00014-07-1-0202. L. Freitag is supported by the ONR grants N00014- 02-6-0201 and N00014-07-1-0229. P. Willett is supported by the ONR grant N00014-07-1-0055
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