scholarly journals Data Gathering from a Multimodal Dense Underwater Acoustic Sensor Network Deployed in Shallow Fresh Water Scenarios

2019 ◽  
Vol 8 (4) ◽  
pp. 55 ◽  
Author(s):  
Alberto Signori ◽  
Filippo Campagnaro ◽  
Fabian Steinmetz ◽  
Bernd-Christian Renner ◽  
Michele Zorzi
Keyword(s):  
Data Collection ◽  
Low Cost ◽  
World Ocean ◽  
Environmental Data ◽  
Sensor Nodes ◽  
Real Field ◽  
Acoustic Sensor ◽  
Adaptive Mechanism ◽  
Underwater Acoustic ◽  
Inspection Service

The Robotic Vessels as-a-Service (RoboVaaS) project intends to exploit the most advanced communication and marine vehicle technologies to revolutionize shipping and near-shore operations, offering on-demand and cost-effective robotic-aided services. In particular, the RoboVaaS vision includes a ship hull inspection service, a quay walls inspection service, an antigrounding service, and an environmental and bathymetry data collection service. In this paper, we present a study of the underwater environmental data collection service, performed by a low-cost autonomous vehicle equipped with both a commercial modem and a very low-cost acoustic modem prototype, the smartPORT Acoustic Underwater Modem (AHOI). The vehicle mules the data from a network of low cost submerged acoustic sensor nodes to a surface sink. To this end, an underwater acoustic network composed by both static and moving nodes has been implemented and simulated with the DESERT Underwater Framework, where the performance of the AHOI modem has been mapped in the form of lookup tables. The performance of the AHOI modem has been measured near the Port of Hamburg, where the RoboVaaS concept will be demonstrated with a real field evaluation. The transmission with the commercial modem, instead, has been simulated with the Bellhop ray tracer thanks to the World Ocean Simulation System (WOSS), by considering both the bathymetry and the sound speed profile of the Port of Hamburg. The set up of the polling-based MAC protocol parameters, such as the maximum backoff time of the sensor nodes, appears to be crucial for the network performance, in particular for the low-cost low-rate modems. In this work, to tune the maximum backoff time during the data collection mission, an adaptive mechanism has been implemented. Specifically, the maximum backoff time is updated based on the network density. This adaptive mechanism results in an 8% improvement of the network throughput.

scholarly journals Robust Silent Localization of Underwater Acoustic Sensor Network Using Mobile Anchor(s)

Sensors ◽  
2021 ◽  
Vol 21 (3) ◽  
pp. 727
Author(s):  
Rahul Mourya ◽  
Mauro Dragone ◽  
Yvan Petillot
Keyword(s):  
Channel Model ◽  
Low Cost ◽  
Sensor Nodes ◽  
Noise Model ◽  
Robust Estimator ◽  
Acoustic Sensor ◽  
Underwater Acoustic ◽  
Acoustic Channel ◽  
Localization Scheme ◽  
Mobile Anchor

Underwater acoustic sensor networks (UWASNs) can revolutionize the subsea domain by enabling low-cost monitoring of subsea assets and the marine environment. Accurate localization of the UWASNs is essential for these applications. In general, range-based localization techniques are preferred for their high accuracy in estimated locations. However, they can be severely affected by variable sound speed, multipath spreading, and other effects of the acoustic channel. In addition, an inefficient localization scheme can consume a significant amount of energy, reducing the effective life of the battery-powered sensor nodes. In this paper, we propose robust, efficient, and practically implementable localization schemes for static UWASNs. The proposed schemes are based on the Time-Difference-of-Arrival (TDoA) measurements and the nodes are localized passively, i.e., by just listening to beacon signals from multiple anchors, thus saving both the channel bandwidth and energy. The robustness in location estimates is achieved by considering an appropriate statistical noise model based on a plausible acoustic channel model and certain practical assumptions. To overcome the practical challenges of deploying and maintaining multiple permanent anchors for TDoA measurements, we propose practical schemes of using a single or multiple surface vehicles as virtual anchors. The robustness of localization is evaluated by simulations under realistic settings. By combining a mobile anchor(s) scheme with a robust estimator, this paper presents a complete package of efficient, robust, and practically usable localization schemes for low-cost UWASNs.

scholarly journals Optimal Deployment of Vector Sensor Nodes in Underwater Acoustic Sensor Networks

Sensors ◽  
2019 ◽  
Vol 19 (13) ◽  
pp. 2885 ◽  
Author(s):  
Sunhyo Kim ◽  
Jee Woong Choi
Keyword(s):  
Sensor Networks ◽  
Particle Velocity ◽  
Sensor Nodes ◽  
Acoustic Sensor ◽  
Underwater Acoustic Sensor Networks ◽  
Communication Performance ◽  
Underwater Acoustic ◽  
Acoustic Sensor Networks ◽  
Vector Sensor ◽  
Optimal Deployment

Underwater acoustic sensor networks have recently attracted considerable attention as demands on the Internet of Underwater Things (IoUT) increase. In terms of efficiency, it is important to achieve the maximum communication coverage using a limited number of sensor nodes while maintaining communication connectivity. In 2017, Kim and Choi proposed a new deployment algorithm using the communication performance surface, which is a geospatial information map representing the underwater acoustic communication performance of a targeted underwater area. In that work, each sensor node was a vertically separated hydrophone array, which measures acoustic pressure (a scalar quantity). Although an array receiver is an effective system to eliminate inter-symbol interference caused by multipath channel impulse responses in underwater communication environments, a large-scale receiver system degrades the spatial efficiency. In this paper, single-vector sensors measuring the particle velocity are used as underwater sensor nodes. A single-vector sensor can be considered to be a single-input multiple-output communication system because it measures the three directional components of particle velocity. Our simulation results show that the optimal deployment obtained using single-vector sensor nodes is more effective than that obtained using a hydrophone (three-channel vertical-pressure sensor) array.

scholarly journals Probabilistic Neighborhood-Based Data Collection Algorithms for 3D Underwater Acoustic Sensor Networks

Sensors ◽  
2017 ◽  
Vol 17 (2) ◽  
pp. 316 ◽  
Author(s):  
Guangjie Han ◽  
Shanshan Li ◽  
Chunsheng Zhu ◽  
Jinfang Jiang ◽  
Wenbo Zhang
Keyword(s):  
Sensor Networks ◽  
Data Collection ◽  
Acoustic Sensor ◽  
Underwater Acoustic Sensor Networks ◽  
Underwater Acoustic ◽  
Acoustic Sensor Networks

scholarly journals DCO-MAC: A Hybrid MAC Protocol for Data Collection in Underwater Acoustic Sensor Networks

Sensors ◽  
2018 ◽  
Vol 18 (7) ◽  
pp. 2300 ◽  
Author(s):  
Min Deng ◽  
Huifang Chen ◽  
Lei Xie
Keyword(s):  
Sensor Networks ◽  
Data Collection ◽  
Mac Protocol ◽  
Heavy Traffic ◽  
Traffic Load ◽  
Acoustic Sensor ◽  
Mobile Nodes ◽  
Underwater Acoustic Sensor Networks ◽  
Underwater Acoustic ◽  
Acoustic Sensor Networks

In underwater acoustic sensor networks (UASNs), medium access control (MAC) is an important issue because of its potentially significant effect on the network performance. However, designing a suitable MAC protocol for the UASN is challenging because of the specific characteristics of the underwater acoustic channel and network, such as limited available bandwidth, long propagation delay, high bit-error-rate, and sparse network topology. In addition, as the traffic load is non-uniformly distributed in a UASN for data collection, it is essential to consider the application feature for the MAC protocol. In this paper, we propose a MAC protocol in a data-collection-oriented UASN, abbreviated as the DCO-MAC protocol. In the proposed protocol, the network is partitioned into two kinds of sub-networks according to the traffic load. A contention-based MAC protocol is used in the sub-network with a light traffic load, while a reservation-based MAC protocol is used in the sub-network with a heavy traffic load. Meanwhile, the DCO-MAC protocol supports the access of mobile nodes. The theoretical analysis and simulation results demonstrate that, in a UASN for data collection, the proposed MAC protocol outperforms the other existing MAC protocols, in terms of the network throughput, end-to-end packet delay, energy overhead, and fairness.

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