Cookies Policy
The website need some cookies and similar means to function. If you permit us, we will use those means to collect data on your visits for aggregated statistics to improve our service. Find out More
Accept Reject
  • Menu
Publications

Publications by Alfredo Martins

2025

From fixed bottom nodes to mobile long term seabed robotic systems: the future of deep ocean observation

Authors
Martins, A; Almeida, J; Almeida, C; Silva, E;

Publication

Abstract
The deep ocean is vast and challenging to observe; however, it is key to knowledge of the sea and its impact on global climate. Fixed sea observing points (such as the EMSO observing nodes) provide a limited view and are complemented by expensive oceanographic campaigns with systems demanding high logistical requirements such as deep-sea ROVs.  These costs not only limit our capability for key ocean data collection in the deep but also introduce their own environmental costs.Emerging challenges in knowledge and pressure on the exploration of the deep ocean demand new technological solutions for monitoring and safeguarding the marine ecosystem.Innovative robotic technologies such as the TURTLE robotic deep-sea landers can combine long-term permanence at the seabed with mobility and dynamic reconfigurability in spatial and temporal deep-sea observation.Robotic systems of a heterogeneous nature (from conventional gliders, AUVs, or robotic landers) can be combined with standard and new sensing systems, such as bottom-deployed sensor nodes, moored systems, and cabled points when feasible.These systems can provide underwater localization services for the different assets, energy supply and high bandwidth data transfer with robotic docking stations for other mobile elements. An example of the synergy obtained with these new systems is the possibility of using robotic landers as carriers of EGIM (EMSO Generic Instrument Module) sensor payloads, providing power and data storage and flexibility in the deployment and recovery process.This approach, partly taken in the EU-funded Trident project to develop technical solutions for cost-effective and efficient observation of environmental impacts on deep seabed environments, allows for a substantial reduction in the operational and logistic requirements for deep-sea observation, greatly reducing the need for costly oceanographic campaigns or the use of expensive (economic and logistical) deep sea ROV systems.In this work, we present some of the new developments and discuss the transition from existing technological solutions to new ones integrating these recent developments.

2025

NETTAG+ - Towards a cleaner fishing practice and reducing the environmental impact of lost fishing gear

Authors
Viegas, D; Martins, A; Neasham, J; Ramos, S; Almeida, M;

Publication

Abstract
Abandoned, Lost, or otherwise Discarded Fishing Gear (ALDFG) has a great impact on marine ecosystems. This is not only due to the direct contribution to marine litter production with particular emphasis on plastics but also to the effects of ghost fishing.The Nettag+ project aims to reduce these impacts by acting on three main lines of action: prevention, avoidance, and mitigation. In the first line, direct action and collaboration with fishers and nature protection organizations around Europe aim to establish the fishermen community as guardians of the ocean. These actions with active fishers' collaboration range from training and dissemination activities related to marine litter and ocean protection to direct measures in day-to-day work to minimize and recover litter from the sea.In the prevention line, an acoustic tag designed explicitly for the location of ALDFG was developed in collaboration with research institutions and fishing gear manufacturers. It can be integrated into the fishing equipment for future tracking and recovery. This tool can reduce lost fishing gear retrieval costs and is complemented with robotic solutions to support retrieving operations.To mitigate the effects of existing untagged ALDFG, multisensorial  detection algorithms are being developed to detect and map ALDFG on the sea and to take advantage of autonomous and robotic systems to perform this task.

  • 22
  • 22