Minimizing deep sea data collection delay with autonomous underwater vehicles

Zheng, Huanyang; Wang, Ning; Wu, Jie

doi:10.1016/j.jpdc.2017.01.006

Cited by 26 publications

(18 citation statements)

References 33 publications

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“…Connectivity of deep-sea species represents another priority conservation consideration. Connectivity plays a key role in the resilience of deep-sea species, populations, communities, and ecosystems following a disturbance event 86 . Analysis of connectivity is particularly important for habitat-forming species, such as deep-water corals, for species that inhabit patchy habitats (e.g.…”

Section: Measuring Essential Variables Needed For Deep-sea Ecosystemsmentioning

confidence: 99%

Ecological variables for developing a global deep-ocean monitoring and conservation strategy

et al. 2020

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The deep sea (>200 m depth) encompasses >95% of the world's ocean volume and represents the largest and least explored biome on Earth (<0.0001% of its surface). It also provides critical climate regulation and other ecosystem services. New species and ecosystems are continuously being discovered in the deep oceans, but commercial fisheries, deep-sea mining, and offshore oil and gas extractions, along with pollution and global change effects, threaten this vast under-explored frontier region. The future of both benthic and pelagic deep-sea ecosystems depends upon effective ecosystembased management strategies enhancing deep-sea conservation, yet we lack consensus on monitoring of the biological and ecological variables that reflect ecosystem status and are needed to support management and environmental decisions at a global scale. Here, we present and discuss the results of an Expert Elicitation of more than 110 deep-sea scientists to prioritize variables and parameters for the future of deep-sea monitoring. We identified five main scientific pillars that need to be further investigated for deep-ocean conservation: i) species and habitat biodiversity, ii) ecosystem function; iii) ecosystem health, impacts, and risk assessment; iv) climate change impacts, the adaptation and evolution of deep-sea life, and v) deep-sea ecosystem conservation. As observing and monitoring can provide the necessary scientific framework for scientists and policy makers to implement effective deep-sea conservation strategies at a global scale, the proposed variables should be further studied in the context of available sensor and other advanced technologies, which are becoming increasingly available.

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Section: Measuring Essential Variables Needed For Deep-sea Ecosystemsmentioning

confidence: 99%

Ecological variables for developing a global deep-ocean monitoring and conservation strategy

et al. 2020

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“…The holding time to guarantee the packet suppression considers the constant value and the estimation of that constant value is impractical in the unpredictable aquatic environment. The sink mobility based schemes are best summarized in the survey in [ 30 ].…”

Section: Previous Workmentioning

confidence: 99%

An Energy Scaled and Expanded Vector-Based Forwarding Scheme for Industrial Underwater Acoustic Sensor Networks with Sink Mobility

Wadud

Hussain

Javaid

et al. 2017

Sensors

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Industrial Underwater Acoustic Sensor Networks (IUASNs) come with intrinsic challenges like long propagation delay, small bandwidth, large energy consumption, three-dimensional deployment, and high deployment and battery replacement cost. Any routing strategy proposed for IUASN must take into account these constraints. The vector based forwarding schemes in literature forward data packets to sink using holding time and location information of the sender, forwarder, and sink nodes. Holding time suppresses data broadcasts; however, it fails to keep energy and delay fairness in the network. To achieve this, we propose an Energy Scaled and Expanded Vector-Based Forwarding (ESEVBF) scheme. ESEVBF uses the residual energy of the node to scale and vector pipeline distance ratio to expand the holding time. Resulting scaled and expanded holding time of all forwarding nodes has a significant difference to avoid multiple forwarding, which reduces energy consumption and energy balancing in the network. If a node has a minimum holding time among its neighbors, it shrinks the holding time and quickly forwards the data packets upstream. The performance of ESEVBF is analyzed through in network scenario with and without node mobility to ensure its effectiveness. Simulation results show that ESEVBF has low energy consumption, reduces forwarded data copies, and less end-to-end delay.

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“…Zheng et al [49] presents a special application of delaytolerant networks (DTNs). Efficient data collection in deep sea poses some unique challenges, due to the need for timely data reporting and the delay of acoustic transmission in the ocean.…”

Section: Related Workmentioning

confidence: 99%

Underwater radio frequency image sensor using progressive image compression and region of interest

Rubino

Centelles

Sales

et al. 2017

J Braz. Soc. Mech. Sci. Eng.

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The increasing demand for underwater robotic intervention systems around the world in several application domains requires more versatile and inexpensive systems. By using a wireless communication system, supervised semi-autonomous robots have freedom of movement; however, the limited and varying bandwidth of underwater radio frequency (RF) channels is a major obstacle for the operator to get camera feedback and supervise the intervention. This paper proposes the use of progressive (embedded) image compression and region of interest (ROI) for the design of an underwater image sensor to be installed in an autonomous underwater vehicle, specially when there are constraints on the available bandwidth, allowing a more agile data exchange between the vehicle and a human operator supervising the underwater intervention. The operator can dynamically decide the size, quality, frame rate, or resolution of the received images so that the available bandwidth is utilized to its fullest potential and with the required minimum latency. The paper focuses first on the description of the system, which uses a camera, an embedded Linux system, and an RF emitter installed in an OpenROV housing cylinder. The RF receiver is connected to a computer on the user side, which controls the camera monitoring parameters, including the compression inputs, such as region of interest (ROI), size of the image, and frame rate. The paper focuses on the compression subsystem and does not attempt to improve the communications physical media for better underwater RF links. Instead, it proposes a unified system that uses well-integrated modules (compression and transmission) to provide the scientific community with a higher-level protocol for image compression and transmission in sub-sea robotic interventions. Keywords Progressive image compression Á Region of interest (ROI) Á Wavelet transforms Á Low-bandwidth communications Á Underwater vehicles for intervention Communicated by Sadek C. Absi Alfaro.

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Minimizing deep sea data collection delay with autonomous underwater vehicles

Cited by 26 publications

References 33 publications

Ecological variables for developing a global deep-ocean monitoring and conservation strategy

Ecological variables for developing a global deep-ocean monitoring and conservation strategy

An Energy Scaled and Expanded Vector-Based Forwarding Scheme for Industrial Underwater Acoustic Sensor Networks with Sink Mobility

Underwater radio frequency image sensor using progressive image compression and region of interest

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