1,134 research outputs found
An accurate RSS/AoA-based localization method for internet of underwater things
Localization is an important issue for Internet of Underwater Things (IoUT) since the performance of a large number of underwater applications highly relies on the position information of underwater sensors. In this paper, we propose a hybrid localization approach based on angle-of-arrival (AoA) and received signal strength (RSS) for IoUT. We consider a smart fishing scenario in which using the proposed approach fishers can find fishes’ locations effectively. The proposed method collects the RSS observation and estimates the AoA based on error variance. To have a more realistic deployment, we assume that the perfect noise information is not available. Thus, a minimax approach is provided in order to optimize the worst-case performance and enhance the estimation accuracy under the unknown parameters. Furthermore, we analyze the mismatch of the proposed estimator using mean-square error (MSE). We then develop semidefinite programming (SDP) based method which relaxes the non-convex constraints into the convex constraints to solve the localization problem in an efficient way. Finally, the Cramer–Rao lower bounds (CRLBs) are derived to bound the performance of the RSS-based estimator. In comparison with other localization schemes, the proposed method increases localization accuracy by more than 13%. Our method can localize 96% of sensor nodes with less than 5% positioning error when there exist 25% anchors
Design of an Optimal Testbed for Tracking of Tagged Marine Megafauna
Underwater acoustic technologies are a key component for exploring the
behavior of marine megafauna such as sea turtles, sharks, and seals. The
animals are marked with acoustic devices (tags) that periodically emit signals
encoding the device's ID along with sensor data such as depth, temperature, or
the dominant acceleration axis - data that is collected by a network of
deployed receivers. In this work, we aim to optimize the locations of receivers
for best tracking of acoustically tagged marine megafauna. The outcomes of such
tracking allows the evaluation of the animals' motion patterns, their hours of
activity, and their social interactions. In particular, we focus on how to
determine the receivers' deployment positions to maximize the coverage area in
which the tagged animals can be tracked. For example, an overly-condensed
deployment may not allow accurate tracking, whereas a sparse one, may lead to a
small coverage area due to too few detections. We formalize the question of
where to best deploy the receivers as a non-convex constraint optimization
problem that takes into account the local environment and the specifications of
the tags, and offer a sub-optimal, low-complexity solution that can be applied
to large testbeds. Numerical investigation for three stimulated sea
environments shows that our proposed method is able to increase the
localization coverage area by 30%, and results from a test case experiment
demonstrate similar performance in a real sea environment. We share the
implementation of our work to help researchers set up their own acoustic
observatory.Comment: Submitted for publication in Frontiers in Marine Science, special
topic on Tracking Marine Megafauna for Conservation and Marine Spatial
Plannin
A Survey on UAV-Aided Maritime Communications: Deployment Considerations, Applications, and Future Challenges
Maritime activities represent a major domain of economic growth with several
emerging maritime Internet of Things use cases, such as smart ports, autonomous
navigation, and ocean monitoring systems. The major enabler for this exciting
ecosystem is the provision of broadband, low-delay, and reliable wireless
coverage to the ever-increasing number of vessels, buoys, platforms, sensors,
and actuators. Towards this end, the integration of unmanned aerial vehicles
(UAVs) in maritime communications introduces an aerial dimension to wireless
connectivity going above and beyond current deployments, which are mainly
relying on shore-based base stations with limited coverage and satellite links
with high latency. Considering the potential of UAV-aided wireless
communications, this survey presents the state-of-the-art in UAV-aided maritime
communications, which, in general, are based on both conventional optimization
and machine-learning-aided approaches. More specifically, relevant UAV-based
network architectures are discussed together with the role of their building
blocks. Then, physical-layer, resource management, and cloud/edge computing and
caching UAV-aided solutions in maritime environments are discussed and grouped
based on their performance targets. Moreover, as UAVs are characterized by
flexible deployment with high re-positioning capabilities, studies on UAV
trajectory optimization for maritime applications are thoroughly discussed. In
addition, aiming at shedding light on the current status of real-world
deployments, experimental studies on UAV-aided maritime communications are
presented and implementation details are given. Finally, several important open
issues in the area of UAV-aided maritime communications are given, related to
the integration of sixth generation (6G) advancements
Underwater 3D positioning on smart devices
The emergence of water-proof mobile and wearable devices (e.g., Garmin
Descent and Apple Watch Ultra) designed for underwater activities like
professional scuba diving, opens up opportunities for underwater networking and
localization capabilities on these devices. Here, we present the first
underwater acoustic positioning system for smart devices. Unlike conventional
systems that use floating buoys as anchors at known locations, we design a
system where a dive leader can compute the relative positions of all other
divers, without any external infrastructure. Our intuition is that in a
well-connected network of devices, if we compute the pairwise distances, we can
determine the shape of the network topology. By incorporating orientation
information about a single diver who is in the visual range of the leader
device, we can then estimate the positions of all the remaining divers, even if
they are not within sight. We address various practical problems including
detecting erroneous distance estimates, addressing rotational and flipping
ambiguities as well as designing a distributed timestamp protocol that scales
linearly with the number of devices. Our evaluations show that our distributed
system running on underwater deployments of 4-5 commodity smart devices can
perform pairwise ranging and localization with median errors of 0.5-0.9 m and
0.9-1.6
Networks, Communication, and Computing Vol. 2
Networks, communications, and computing have become ubiquitous and inseparable parts of everyday life. This book is based on a Special Issue of the Algorithms journal, and it is devoted to the exploration of the many-faceted relationship of networks, communications, and computing. The included papers explore the current state-of-the-art research in these areas, with a particular interest in the interactions among the fields
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