Probabilistic Spatially-Divided Multiple Access in Underwater Acoustic Sparse Networks

2019 IEEE 16th International Conference on Mobile Ad Hoc and Sensor Systems (MASS)

Pompili

2019

Self Cite

Underwater imagery has enabled numerous civilian applications in various domains, ranging from academia to industry, and from industrial surveillance and maintenance to environmental protection and behavior of marine creatures studies. The accumulation of litter and plastic debris at the seafloor and the bottom of rivers are extremely harmful for the aquatic life. We propose a solution for monitoring this problem using a team of Autonomous Underwater Vehicles (AUVs) to exchange the recorded video in order to reconstruct the map of regions of interest. However, underwater video transmission is a challenge in the harsh environment in which radio-frequency waves are absorbed for distances above a few tens of meters, optical waves require narrow laser beams and suffer from scattering and ocean wave motion, and acoustic waves-while long range-provide a very low bandwidth and unreliable channel for communication. In our solution, the scalable coded video of each vehicle is shared in-network with a selected group of receiving vehicles through the underwater acoustic channel. Presented evaluations, including both simulations and experiments, confirm the efficiency and flexibility of the proposed solution using acoustic software-defined modems.

Section: A Construction Of Svc-encoded Video Streamsmentioning

confidence: 99%

Section: B Multicasting For Enhancement-layer Video Sharingmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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UW-SVC: Scalable Video Coding Transmission for In-Network Underwater Imagery Analysis

2019 IEEE 16th International Conference on Mobile Ad Hoc and Sensor Systems (MASS)

Pompili

2019

Self Cite

“…Overview: Underwater networks enable various applications such as oceanographic data collection, pollution monitoring [10], and disaster prevention using static nodes [8] and/or mobile vehicles [9]. In many applications, we need mobile vehicles, equipped with appropriate on-board sensors, rather than static nodes in order to traverse the area and measure the required parameters across the regions of interest, since static nodes pose many limitations [7] in applications such as adaptive sampling.…”

Section: Introductionmentioning

confidence: 99%

Uw-Marl

Proceedings of the International Conference on Underwater Networks &Amp; Systems

Nadeem

Sadhu

et al. 2019

Self Cite

Near-real-time water-quality monitoring in uncertain environments such as rivers, lakes, and water reservoirs of different variables is critical to protect the aquatic life and to prevent further propagation of the potential pollution in the water. In order to measure the physical values in a region of interest, adaptive sampling is helpful as an energy-and time-efficient technique since an exhaustive search of an area is not feasible with a single vehicle. We propose an adaptive sampling algorithm using multiple autonomous vehicles, which are well-trained, as agents, in a Multi-Agent Reinforcement Learning (MARL) framework to make efficient sequence of decisions on the adaptive sampling procedure. The proposed solution is evaluated using experimental data, which is fed into a simulation framework. Experiments were conducted in the Raritan River, Somerset and in Carnegie Lake, Princeton, NJ during July 2019.

“…The uncertainty region is modeled for networked autonomous vehicles as in [8]. An Unscented Kalman Filter (UKF) is applied to the uncertainty model to improve the precision and to reduce the uncertainty of the model [11]. Authors in [5] use Kalman filtering to approximate the trajectory of a vehicle, such that the vehicle only have to report its trajectory when there is an adjustment in it.…”

Section: Introductionmentioning

confidence: 99%

Compressed Underwater Acoustic Communications for Dynamic Interaction with Underwater Vehicles

Proceedings of the International Conference on Underwater Networks &Amp; Systems

Arjula

Pompili

2019

Self Cite

Underwater vehicles are utilized in various applications including underwater data-collection missions. The tethered connection constrains the mission both in distance traveled and number of vehicles that can run in the same area, while the addition of acoustic communications onto the vehicles grants them several functionalities. However, due to the low bandwidth of the underwater acoustic channel-which leads to low data rates-and the time overhead imposed by both the channel propagation delay and the processing delay by the acoustic modems, efficient protocols are required. In this paper, an implicit data-compression and transmission protocol is proposed to carry out environmental monitoring missions such as adaptive sampling of physical and chemical parameters in the water. In a semi-autonomous manner between the vehicle and the control center, both sides keep silent in data transmission as long as they can estimate and predict the actions of the other side, unless environmental data and/or kinematic data are found to be unpredictable. Our design puts the human in the loop to send high-level control commands. Experiments were conducted using an autonomous vehicle with WHOI micro-modems in the Raritan River, Somerset, Carnegie Lake in Princeton, and in the Marine Park in Red Bank, all in New Jersey.