250 research outputs found
EFFICIENT CAMERA SELECTION FOR MAXIMIZED TARGET COVERAGE IN UNDERWATER ACOUSTIC SENSOR NETWORKS
In Underwater Acoustic Sensor Networks (UWASNs), cameras have recently been deployed for enhanced monitoring. However, their use has faced several obstacles. Since video capturing and processing consume significant amounts of camera battery power, they are kept in sleep mode and activated only when ultrasonic sensors detect a target. The present study proposes a camera relocation structure in UWASNs to maximize the coverage of detected targets with the least possible vertical camera movement. This approach determines the coverage of each acoustic sensor in advance by getting the most applicable cameras in terms of orientation and frustum of camera in 3-D that are covered by such sensors. Whenever a target is exposed, this information is then used and shared with other sensors that detected the same target. Compared to a flooding-based approach, experiment results indicate that this proposed solution can quickly capture the detected targets with the least camera movement
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
Game Theory-Based Cooperation for Underwater Acoustic Sensor Networks: Taxonomy, Review, Research Challenges and Directions.
Exploring and monitoring the underwater world using underwater sensors is drawing a lot of attention these days. In this field cooperation between acoustic sensor nodes has been a critical problem due to the challenging features such as acoustic channel failure (sound signal), long propagation delay of acoustic signal, limited bandwidth and loss of connectivity. There are several proposed methods to improve cooperation between the nodes by incorporating information/game theory in the node's cooperation. However, there is a need to classify the existing works and demonstrate their performance in addressing the cooperation issue. In this paper, we have conducted a review to investigate various factors affecting cooperation in underwater acoustic sensor networks. We study various cooperation techniques used for underwater acoustic sensor networks from different perspectives, with a concentration on communication reliability, energy consumption, and security and present a taxonomy for underwater cooperation. Moreover, we further review how the game theory can be applied to make the nodes cooperate with each other. We further analyze different cooperative game methods, where their performance on different metrics is compared. Finally, open issues and future research direction in underwater acoustic sensor networks are highlighted
Distributed navigation of multi-robot systems for sensing coverage
A team of coordinating mobile robots equipped with operation specific sensors can
perform different coverage tasks. If the required number of robots in the team is
very large then a centralized control system becomes a complex strategy. There
are also some areas where centralized communication turns into an issue. So, a
team of mobile robots for coverage tasks should have the ability of decentralized or
distributed decision making. This thesis investigates decentralized control of mobile
robots specifically for coverage problems. A decentralized control strategy is ideally
based on local information and it can offer flexibility in case there is an increment
or decrement in the number of mobile robots. We perform a broad survey of the
existing literature for coverage control problems. There are different approaches
associated with decentralized control strategy for coverage control problems. We
perform a comparative review of these approaches and use the approach based on
simple local coordination rules. These locally computed nearest neighbour rules are
used to develop decentralized control algorithms for coverage control problems.
We investigate this extensively used nearest neighbour rule-based approach for
developing coverage control algorithms. In this approach, a mobile robot gives an
equal importance to every neighbour robot coming under its communication range.
We develop our control approach by making some of the mobile robots playing
a more influential role than other members of the team. We develop the control
algorithm based on nearest neighbour rules with weighted average functions. The
approach based on this control strategy becomes efficient in terms of achieving a
consensus on control inputs, say heading angle, velocity, etc.
The decentralized control of mobile robots can also exhibit a cyclic behaviour
under some physical constraints like a quantized orientation of the mobile robot.
We further investigate the cyclic behaviour appearing due to the quantized control
of mobile robots under some conditions. Our nearest neighbour rule-based approach
offers a biased strategy in case of cyclic behaviour appearing in the team of mobile
robots.
We consider a clustering technique inside the team of mobile robots. Our decentralized
control strategy calculates the similarity measure among the neighbours
of a mobile robot. The team of mobile robots with the similarity measure based
approach becomes efficient in achieving a fast consensus like on heading angle or
velocity. We perform a rigorous mathematical analysis of our developed approach.
We also develop a condition based on relaxed criteria for achieving consensus on
velocity or heading angle of the mobile robots. Our validation approach is based on
mathematical arguments and extensive computer simulations
Covering Points of Interest with Mobile Sensors
International audienceThe coverage of Points of Interest (PoI) is a classical requirement in mobile wireless sensor applications. Optimizing the sensors self-deployment over a PoI while maintaining the connectivity between the sensors and the base station is thus a fundamental issue. This article addresses the problem of autonomous deployment of mobile sensors that need to cover a predefined PoI with a connectivity constraint. In our algorithm, each sensor moves toward a PoI but has also to maintain the connectivity with a subset of its neighboring sensors that are part of the Relative Neighborhood Graph (RNG). The Relative Neighborhood Graph reduction is chosen so that global connectivity can be provided locally. Our deployment scheme minimizes the number of sensors used for connectivity thus increasing the number of monitoring sensors. Analytical results, simulation results and practical implementation are provided to show the efficiency of our algorithm
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