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About

Raul Manuel Morais Pereira dos Santos graduated in Electrical Engineering (branch of Electronics, Instrumentation and Computer Science) at the University of Trás-Os-Montes e Alto Douro (UTAD), Portugal, in 1993. He obtained his Master's degree in Industrial Electronics from the University of Minho in 1998 and a PhD degree in Electrical and Computer Engineering (specialty microelectronics) obtained from UTAD in 2004. His aggregation in Electrical and Computer Engineering was obtained in UTAD in 2009. He is currently an Associate Professor with Habilitation at the Engineering Department of the School of Science and Technology of UTAD. His main areas of interest include sensors and sensor interfaces in CMOS microelectronics, energy harvesting techniques to power small and unattended electronic devices and wireless sensor networks in the context of agriculture/precision viticulture. Another area of interest is in the field of biomedical implantable devices, especially in biotelemetry systems regarding vibration microgenerators to produce electric energy inside smart prosthesis. He is currently an integrated member of the Institute of Integrated Systems and Computer Engineering of Porto (INESC-TEC).

Interest
Topics
Details

Details

003
Publications

2019

Localization Based on Natural Features Detector for Steep Slope Vineyards

Authors
Mendes, JM; dos Santos, FN; Ferraz, NA; do Couto, PM; dos Santos, RM;

Publication
Journal of Intelligent and Robotic Systems: Theory and Applications

Abstract
Placing ground robots to work in steep slope vineyards is a complex challenge. The Global Positioning System (GPS) signal is not always available and accurate. A reliable localization approach to detect natural features for this environment is required. This paper presents an improved version of a visual detector for Vineyards Trunks and Masts (ViTruDe) and, a robot able to cope pruning actions in steep slope vineyards (AgRob V16). In addition, it presents an augmented data-set for other localization and mapping algorithm benchmarks. ViTruDe accuracy is higher than 95% under our experiments. Under a simulated runtime test, the accuracy lies between 27% - 96% depending on ViTrude parametrization. This approach can feed a localization system to solve a GPS signal absence. The ViTruDe detector also considers economic constraints and allows to develop cost-effective robots. The augmented training and datasets are publicly available for future research work. © 2018 Springer Science+Business Media B.V., part of Springer Nature

2018

Distributed monitoring system for precision enology of the Tawny Port wine aging process

Authors
Morais, R; Peres, E; Boaventura Cunha, J; Mendes, J; Cosme, F; Nunes, FM;

Publication
Computers and Electronics in Agriculture

Abstract

2018

Application of bioelectrical impedance analysis in prediction of light kid carcass and muscle chemical composition

Authors
Silva, SR; Afonso, J; Monteiro, A; Morais, R; Cabo, A; Batista, AC; Guedes, CM; Teixeira, A;

Publication
animal

Abstract
Carcass data were collected from 24 kids (average live weight of 12.5±5.5 kg; range 4.5 to 22.4 kg) of Jarmelista Portuguese native breed, to evaluate bioelectrical impedance analysis (BIA) as a technique for prediction of light kid carcass and muscle chemical composition. Resistance (Rs, ?) and reactance (Xc, ?), were measured in the cold carcasses with a single frequency bioelectrical impedance analyzer and, together with impedance (Z, ?), two electrical volume measurements (VolA and VolB, cm2/O), carcass cold weight (CCW), carcass compactness and several carcass linear measurements were fitted as independent variables to predict carcass composition by stepwise regression analysis. The amount of variation explained by VolA and VolB only reached a significant level (P<0.01 and P<0.05, respectively) for muscle weight, moisture, protein and fat-free soft tissue content, even so with low accuracy, with VolA providing the best results (0.326?R 2?0.366). Quite differently, individual BIA parameters (Rs, Xc and Z) explained a very large amount of variation in dissectible carcass fat weight (0.814?R 2?0.862; P<0.01). These individual BIA parameters also explained a large amount of variation in subcutaneous and intermuscular fat weights (respectively 0.749?R 2?0.793 and 0.718?R 2?0.760; P<0.01), and in muscle chemical fat weight (0.663?R 2?0.684; P<0.01). Still significant but much lower was the variation in muscle, moisture, protein and fat-free soft tissue weights (0.344?R 2?0.393; P<0.01) explained by BIA parameters. Still, the best models for estimation of muscle, moisture, protein and fat-free soft tissue weights included Rs in addition to CCW, and accounted for 97.1% to 99.8% (P<0.01) of the variation observed, with CCW by itself accounting for 97.0% to 99.6% (P<0.01) of that variation. Resistance was the only independent variable selected for the best model predicting subcutaneous fat weight. It was also selected for the best models predicting carcass fat weight (combined with carcass length, CL; R 2=0.943; P<0.01) and intermuscular fat weight (combined with CCW; R 2=0.945; P<0.01). The best model predicting muscle chemical fat weight combined CCW and Z, explaining 85.6% (P<0.01) of the variation observed. These results indicate BIA as a useful tool for prediction of light kids’ carcass composition.

2018

Machine learning classification methods in hyperspectral data processing for agricultural applications

Authors
Hruska, J; Adão, T; Pádua, L; Marques, P; Cunha, A; Peres, E; Sousa, AMR; Morais, R; Sousa, JJ;

Publication
Proceedings of the International Conference on Geoinformatics and Data Analysis - ICGDA '18

Abstract

2018

UAS-based imagery and photogrammetric processing for tree height and crown diameter extraction

Authors
Pádua, L; Marques, P; Adão, T; Hruska, J; Peres, E; Morais, R; Sousa, AMR; Sousa, JJ;

Publication
Proceedings of the International Conference on Geoinformatics and Data Analysis - ICGDA '18

Abstract

Supervised
thesis

2017

Interfaces para sistemas de domótica

Author
Tiago Manuel Afonso Porto

Institution
UTAD

2017

Sistemas de domótica sobre tecnologias sem fios wi-fi

Author
Jorge Miguel Carvalho Gonçalves

Institution
UTAD

2017

Avaliação de atividade muscular através de eletromiografia

Author
Inês Filipa Vaz da Silva

Institution
UTAD

2016

Sistema de monitorização do fluxo de seiva em videira

Author
Bárbara Filipa de Carvalho Góis

Institution
UTAD

2016

NAVEGAÇÃO AUTÓNOMA EM TERRENO VINHATEIRO

Author
Olga Maria de Sousa Contente

Institution
UTAD