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

Abstract

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.

Cosmic time synchronizer (CTS) for wireless and precise time synchronization using extended air showers

“…Another possibility to both benefit and share the CTS time synchronization capability would be time synchronization operation in a dense underwater sensor network (USN) (more than a few hundred nodes per square meter). For example, this kind of dense USN could be associated with the Robotic Vessels as-a-Service (RoboVaaS) project, which is a new scheme aiming at revolutionizing near-shore operations in coastal waters by integrating and networking a smaller Unmanned Surface Vehicle (USV) and an Unmanned Underwater Vehicle (UUV) efficiently in order to offer new services for shipping 55 . In order to safely operate RoboVaaS, the environmental data are collected by a dense USN, which will inspect the impact to RoboVaaS, as well as to monitor the coastal conditions 56 .…”

Wireless Muometric Navigation System

“…In this case, a shallow bay (< 20 m) such as Tokyo Bay was chosen as an example, and a new scheme called the Robotic Vessels as-a-Service (RoboVaaS) was considered. RoboVaaS is a new scheme which intends to revolutionize shipping and near-shore operations in coastal waters by integrating and networking a smaller Unmanned Surface Vehicle (USV) and an Unmanned Underwater Vehicle (UUV) e ciently in order to offer new services for shipping 42 . In this scheme, it was assumed that a number of USVs that carry reference detectors would navigate a number of UUVs operated at a depth of 15 m below sea level.…”

An Event-Based Stack For Data Transmission Through Underwater Multimodal Networks

“…We quantify the performance loss with each possible hardware configuration, proving that the system can be employed for real data transmission in multihop multimodal underwater networks, at the price of an almost negligible performance loss due to the DESERT processing time. Future work will focus on the evaluation of a complete multimodal network composed by both S2C and AHOI modems, as well as wireless surface links in real field tests to perform data gathering from underwater sensors [22] in the context of the RoBoVaaS project [23] and the ability to optimally exploit modem-specific features such as the S2C burst data transmission.…”