Multi-sensor 3D mapping of Tethys Bay (Ross Sea – Antarctica) with PROTEUS, an innovative, highly reconfigurable and versatile unmanned marine vehicle

Aracri, Simona; Bibuli, Marco; Bruzzone, Gabriele; Caccia, M.; Ferretti, R.; Giacopelli, Mauro; Ivaldi, Roberta; Motta, Corrado; Odetti, Angelo; Spirandelli, E.; Zereik, Enrica

doi:10.5194/egusphere-egu23-12041

Cited by 2 publications

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“…In the context of developing a prototype for monitoring alpine lakes, recent polar expeditions led by the CNR-INM demonstrated an increasing demand for technological tools to monitor fragile ecosystems in remote regions affected by human activities [19][20][21][22]. Data scarcity hinders both the understanding of environmental processes and the implementation of conservation actions.…”

Section: Background Motivation and Objectivesmentioning

confidence: 99%

Lake Environmental Data Harvester (LED) for Alpine Lake Monitoring with Autonomous Surface Vehicles (ASVs)

Odetti,

Bruzzone,

Ferretti

et al. 2024

Remote Sensing

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This article introduces the Lake Environmental Data Harvester (LED) System, a robotic platform designed for the development of an innovative solution for monitoring remote alpine lakes. LED is intended as the first step in creating portable robotic tools that are lightweight, cost-effective, and highly reliable for monitoring remote water bodies. The LED system is based on the Shallow-Water Autonomous Multipurpose Platform (SWAMP), a groundbreaking Autonomous Surface Vehicle (ASV) originally designed for monitoring wetlands. The objective of LED is to achieve the comprehensive monitoring of remote lakes by outfitting the SWAMP with a suite of sensors, integrating an IoT infrastructure, and adhering to FAIR principles for structured data management. SWAMP’s modular design and open architecture facilitate the easy integration of payloads, while its compact size and construction with a reduced weight ensure portability. Equipped with four azimuth thrusters and a flexible hull structure, SWAMP offers a high degree of maneuverability and position-keeping ability for precise surveys in the shallow waters that are typical of remote lakes. In this project, SWAMP was equipped with a suite of sensors, including a single-beam dual-frequency echosounder, water-quality sensors, a winch for sensor deployment, and AirQino, a low-cost air quality analysis system, along with an RTK-GNSS (Global Navigation Satellite System) receiver for precise positioning. Utilizing commercial off-the-shelf (COTS) components, a Multipurpose Data-Acquisition System forms the basis for an Internet of Things (IoT) infrastructure, enabling data acquisition, storage, and long-range communication. This data-centric system design ensures that acquired variables from both sensors and the robotic platform are structured and managed according to the FAIR principles.

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Section: Background Motivation and Objectivesmentioning

confidence: 99%

Lake Environmental Data Harvester (LED) for Alpine Lake Monitoring with Autonomous Surface Vehicles (ASVs)

Odetti,

Bruzzone,

Ferretti

et al. 2024

Remote Sensing

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A framework for FAIR robotic datasets

Motta,

Aracri,

Ferretti

et al. 2023

Sci Data

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It is essential to publish and make available environmental data gathered by emerging robotic platforms to contribute to the Global Ocean Observing System (GOOS), supported by the United Nations - Decade of Ocean Science for Sustainable Development (2021–2030). The transparency of these unique observational datasets needs to be supported by the corresponding robotic records. The data describing the observational platform behaviour and its performance are necessary to validate the environmental data and repeat consistently the in-situ robotic deployment. The Free and Open Source Software (FOSS), proposed in this manuscript, describes how, using the established approach in Earth Sciences, the data characterising marine robotic missions can be formatted and shared following the FAIR (Findable, Accessible, Interoperable, Reusable) principles. The manuscript is a step-by-step guide to render marine robotic telemetry FAIR and publishable. State-of-the-art protocols for metadata and data formatting are proposed, applied and integrated automatically using Jupyter Notebooks to maximise visibility and ease of use. The method outlined here aims to be a first fundamental step towards FAIR interdisciplinary observational science.

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Multi-sensor 3D mapping of Tethys Bay (Ross Sea – Antarctica) with PROTEUS, an innovative, highly reconfigurable and versatile unmanned marine vehicle

Cited by 2 publications

References 0 publications

Lake Environmental Data Harvester (LED) for Alpine Lake Monitoring with Autonomous Surface Vehicles (ASVs)

Lake Environmental Data Harvester (LED) for Alpine Lake Monitoring with Autonomous Surface Vehicles (ASVs)

A framework for FAIR robotic datasets

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