Desde01 maio 2004
CentroCentro de Robótica e Sistemas Autónomos
Preventing, avoiding and mitigating environmental impacts of fishing gears and associated marine litter
Modular Platform for Research, Test and Validation of Technologies supporting a Sustainable Blue Economy
Desenvolvimento de uma nova tecnologia para cultivo de larvas de peixes à primeira alimentação
Conectar os Oceanos Atlântico e Ártico para Decifrar o Impacto das Alterações Climática nas Funções dos Microbiomas Planctónicos
Technology based impact assessment tool foR sustaInable, transparent Deep sEa miNing exploraTion and exploitation
Teixeira, B; Lima, AP; Pinho, C; Viegas, D; Dias, N; Silva, H; Almeida, J;
2022 OCEANS HAMPTON ROADS
The Feedfirst Intelligent Monitoring System is a novel tool for intelligent monitoring of fish nurseries in aquaculture scenarios, mainly focusing on monitoring three essential items: water quality control, biomass estimation, and automated feeding. The system is based on machine vision techniques for fish larvae population size detection, and larvae biomass estimation is monitored through size measurement. We also show that the perception-actuation loop in automated fish tanks can be closed by using the vision system output to influence feeding procedures. The proposed solution was tested in a real tank in an aquaculture setting with real-time performance and logging capabilities.
Freitas, S; Silva, H; Almeida, C; Viegas, D; Amaral, A; Santos, T; Dias, A; Jorge, PAS; Pham, CK; Moutinho, J; Silva, E;
OCEANS 2021: SAN DIEGO - PORTO
This work addresses the use of hyperspectral imaging systems for remote detection of marine litter concentrations in oceanic environments. The work consisted on mounting an off-the-shelf hyperspectral imaging system (400-2500 nm) in two aerial platforms: manned and unmanned, and performing data acquisition to develop AI methods capable of detecting marine litter concentrations at the water surface. We performed the campaigns at Porto Pim Bay, Fail Island, Azores, resorting to artificial targets built using marine litter samples. During this work, we also developed a Convolutional Neural Network (CNN-3D), using spatial and spectral information to evaluate deep learning methods to detect marine litter in an automated manner. Results show over 84% overall accuracy (OA) in the detection and classification of the different types of marine litter samples present in the artificial targets.
Martins, A; Almeida, C; Lima, P; Viegas, D; Silva, J; Almeida, JM; Almeida, C; Ramos, S; Silva, E;
GLOBAL OCEANS 2020: SINGAPORE - U.S. GULF COAST
This paper presents an autonomous robotic system, IRIS, designed for lost fishing gear recovery. The vehicle was developed in the context of the NetTag project. This is a European Union project funded by EASME the Executive Agency for Small and Medium Enterprises addressing marine litter, and the reduction of quantity and impact of lost fishing gears in the ocean. NetTag intends to produce new technological devices for location and recovery of fishing gear and educational material about marine litter, raise awareness of fisheries industry and other stakeholders about the urgent need to combat marine litter and increase scientific knowledge on marine litter problematic, guaranteeing the engagement of fishers to adopt better practices to reduce and prevent marine litter derived from fisheries. The design of IRIS is presented in detail, addressing the mechanical design, hardware architecture, sensor system and navigation and control. Preliminary tests in tank and in controlled sea conditions are presented and ongoing developments on the recovery system are discussed.
Coelho, L; Agostinho Moreira, JA; Tavares, PB; Santos, JL; Viegas, D; de Almeida, JMMM;
SENSORS AND ACTUATORS A-PHYSICAL
Long period fiber gratings (LPFGs) were used to monitor the characteristics of copper (Cu) thin films when annealed in air atmosphere up to similar to 680 degrees C. The wavelength and the optical power shift of the resonant bands of the LPFGs when coated with the Cu thin films, were measured as a function of the annealing temperature, and were found to exhibit a different evolution comparing to a bare LPFGs. Thin films of Cu deposited on quartz (SiO2) substrates were annealed and analyzed by XRD, SEM/EDS and Raman spectroscopy, allowing to identify the formation of two distinct oxide phases at different temperatures, cuprous (Cu2O-cuprite) and cupric (CuO-tenorite) oxides, respectively. The observed features of the resonant bands of the LPFGs were found to be associated with the Cu oxide phase transitions, indicating the possibility of using LPFGs to monitor, in real time, the oxidation states of Cu thin films by following specific characteristics of the attenuation bands. In addition, LPFGs over coated with the two distinct oxidation phases of Cu were characterized for refractive index sensing in the range between 1.300 to 1.600, leading to the conclusion that the sensitivity to the refractive index of the surrounding medium of Cu coated LPFGs sensing systems can be temperature tuned.
Moayyed, H; Leite, IT; Coelho, L; Santos, JL; Viegas, D;
MEASUREMENT SCIENCE AND TECHNOLOGY
This work reports the theoretical investigation of optical fiber surface plasmon resonance sensors incorporating bimetallic layer combinations. Different metals like silver, gold, copper, and aluminum are considered to investigate the refractometric sensing properties of tapered and tip optrode phase-interrogated optical fiber plasmonic sensor structures. It is shown that the gold-silver combination, coupled to a tip optrode layout, is capable of maximizing the resolution and operation range of these sensing structures for environmental refractive index measurement.
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