Cookies
Usamos cookies para melhorar nosso site e a sua experiência. Ao continuar a navegar no site, você aceita a nossa política de cookies. Ver mais
Aceitar Rejeitar
  • Menu
Sobre
Download foto HD

Sobre

Raul Manuel Pereira Morais dos Santos licenciou-se em Engenharia Electrotécnica (Ramo de Electrónica, Instrumentação e Computação), pela Universidade de Trás-os-Montes e Alto Douro (UTAD), Portugal, em 1993. Obteve o grau de Mestre em Electrónica Industrial pela Universidade do Minho, em 1998. O seu doutoramento, em Engenharia Electrotécnica e de Computadores, especialidade de microeletrónica, foi obtido na UTAD, em 2004. A sua Agregação em Engenharia Electrotécnica e de Computadores foi obtida na UTAD em 2009. Atualmente é Professor Associado com Agregação no Departamento de Engenharias da Escola de Ciências e Tecnologia da UTAD. As suas principais áreas de interesse incluem: sensores e interfaces sensoriais em microeletrónica, técnicas de recolha de energia para alimentação de dispositivos eletrónicos e redes de sensores sem fios em contextos de agricultura/viticultura de precisão. Tem também interesses no campo dos dispositivos biomédicos implantáveis, em particular nos sistemas de biotelemetria e nos microgeradores vibracionais para produção de energia no interior de dispositivos implantáveis. É atualmente membro integrado no Instituto de Engenharia de Sistemas e Computadores do Porto (INESC-TEC)

Tópicos
de interesse
Detalhes

Detalhes

003
Publicações

2020

Smartphone Applications Targeting Precision Agriculture Practices—A Systematic Review

Autores
Mendes, J; Pinho, TM; dos Santos, FN; Sousa, JJ; Peres, E; Boaventura Cunha, J; Cunha, M; Morais, R;

Publicação
Agronomy

Abstract
Traditionally farmers have used their perceptual sensorial systems to diagnose and monitor their crops health and needs. However, humans possess five basic perceptual systems with accuracy levels that can change from human to human which are largely dependent on the stress, experience, health and age. To overcome this problem, in the last decade, with the help of the emergence of smartphone technology, new agronomic applications were developed to reach better, cost-effective, more accurate and portable diagnosis systems. Conventional smartphones are equipped with several sensors that could be useful to support near real-time usual and advanced farming activities at a very low cost. Therefore, the development of agricultural applications based on smartphone devices has increased exponentially in the last years. However, the great potential offered by smartphone applications is still yet to be fully realized. Thus, this paper presents a literature review and an analysis of the characteristics of several mobile applications for use in smart/precision agriculture available on the market or developed at research level. This will contribute to provide to farmers an overview of the applications type that exist, what features they provide and a comparison between them. Also, this paper is an important resource to help researchers and applications developers to understand the limitations of existing tools and where new contributions can be performed.

2020

Utilization of Bioelectrical Impedance to Predict Intramuscular Fat and Physicochemical Traits of the Beef Longissimus Thoracis et Lumborum Muscle

Autores
Afonso, J; Guedes, C; Santos, V; Morais, R; Silva, J; Teixeira, A; Silva, S;

Publicação
FOODS

Abstract
The bioelectrical impedance analysis (BIA) is a non-destructive technique that has been successfully used to assess the body and carcass composition of farm species. This study aimed to predict intramuscular fat (IMF) and physicochemical traits in the longissimus thoracis et lumborum muscle (LM) of beef, using BIA. These traits were evaluated in LM samples of 52 crossbred heifer carcasses. The BIA was performed in LM, using a 50 Hz frequency high precision impedance converter system. A correlation analysis of the studied variables was performed. Then a stepwise with a k-folds cross validation procedure was used to modelling the prediction of IMF and physicochemical traits from BIA parameters (24.5% <= CV <= 47.3%). Wide variation was found for IMF and BIA parameters. In general, correlations of BIA parameters with IMF and physicochemical traits were moderate to high and were similar for all BIA parameters (-0.50 <= r <= 0.50 only for total pigments, a* and pH48). It was possible to predict IMF and physicochemical traits from BIA. The best fit explained 79.3% of the variation in IMF, while for physicochemical traits the best fits were for sarcomere length and shear force (64.4% and 60.5%, respectively). The results confirmed the potential of BIA for objective measurement of meat quality.

2019

Localization Based on Natural Features Detector for Steep Slope Vineyards

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

Publicação
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

2019

mySense: A comprehensive data management environment to improve precision agriculture practices

Autores
Morais, R; Silva, N; Mendes, J; Adao, T; Padua, L; Lopez Riquelme, J; Pavon Pulido, N; Sousa, JJ; Peres, E;

Publicação
Computers and Electronics in Agriculture

Abstract

2019

Digital Ampelographer: A CNN Based Preliminary Approach

Autores
Adão, T; Pinho, TM; Ferreira, A; Sousa, AMR; Pádua, L; Sousa, J; Sousa, JJ; Peres, E; Morais, R;

Publicação
Progress in Artificial Intelligence - Lecture Notes in Computer Science

Abstract

Teses
supervisionadas

2019

Estudo e aplicação de modelos de previsão de doenças da vinha sobre plataformas de IOT

Autor
Carlos Manuel Olo Peixoto

Instituição
UTAD

2019

Contribuição para o estudo dos músculos da mastigação em modelo animal com doença degenerativa das articulações temporomandibulares

Autor
Cláudia Sofia Barbosa da Costa Ribeiro

Instituição
UP-FMDUP

2019

Desenvolvimento de uma aplicação androoide para o jardim botânico da Utad

Autor
João Carlos Trindade Moreira

Instituição
UTAD

2019

Self-adaptive electromagnetic energy harvesting system

Autor
Pedro Miguel Rocha Carneiro

Instituição
IES_Outra

2019

Sistemas de telecontagem para a monitorização do consumo de água

Autor
Renato José Moura da Silva

Instituição
UTAD