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Open AccessArticle

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

1
Department of Information Engineering, University of Padua, 35131 Padua, Italy
2
Research Group smartPORT, Hamburg University of Technology, 21073 Hamburg, Germany
*
Author to whom correspondence should be addressed.
J. Sens. Actuator Netw. 2019, 8(4), 55; https://doi.org/10.3390/jsan8040055
Received: 30 September 2019 / Revised: 16 November 2019 / Accepted: 27 November 2019 / Published: 30 November 2019
(This article belongs to the Special Issue Underwater Networking)
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. View Full-Text
Keywords: underwater multimodal sensor networks; underwater acoustic networks; polling protocol; AHOI modem; DESERT Underwater network simulations; Bellhop ray tracer; WOSS underwater multimodal sensor networks; underwater acoustic networks; polling protocol; AHOI modem; DESERT Underwater network simulations; Bellhop ray tracer; WOSS
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MDPI and ACS Style

Signori, A.; Campagnaro, F.; Steinmetz, F.; Renner, B.-C.; Zorzi, M. Data Gathering from a Multimodal Dense Underwater Acoustic Sensor Network Deployed in Shallow Fresh Water Scenarios. J. Sens. Actuator Netw. 2019, 8, 55.

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