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About

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

2022

Vineyard classification using OBIA on UAV-based RGB and multispectral data: A case study in different wine regions

Authors
Padua, L; Matese, A; Di Gennaro, SF; Morais, R; Peres, E; Sousa, JJ;

Publication
COMPUTERS AND ELECTRONICS IN AGRICULTURE

Abstract

2022

VineInspector: The Vineyard Assistant

Authors
Mendes, J; Peres, E; dos Santos, FN; Silva, N; Silva, R; Sousa, JJ; Cortez, I; Morais, R;

Publication
AGRICULTURE-BASEL

Abstract
Proximity sensing approaches with a wide array of sensors available for use in precision viticulture contexts can nowadays be considered both well-know and mature technologies. Still, several in-field practices performed throughout different crops rely on direct visual observation supported on gained experience to assess aspects of plants’ phenological development, as well as indicators relating to the onset of common plagues and diseases. Aiming to mimic in-field direct observation, this paper presents VineInspector: a low-cost, self-contained and easy-to-install system, which is able to measure microclimatic parameters, and also to acquire images using multiple cameras. It is built upon a stake structure, rendering it suitable for deployment across a vineyard. The approach through which distinguishable attributes are detected, classified and tallied in the periodically acquired images, makes use of artificial intelligence approaches. Furthermore, it is made available through an IoT cloud-based support system. VineInspector was field-tested under real operating conditions to assess not only the robustness and the operating functionality of the hardware solution, but also the AI approaches’ accuracy. Two applications were developed to evaluate VineInspector’s consistency while a viticulturist’ assistant in everyday practices. One was intended to determine the size of the very first grapevines’ shoots, one of the required parameters of the well known 3–10 rule to predict primary downy mildew infection. The other was developed to tally grapevine moth males captured in sex traps. Results show that VineInspector is a logical step in smart proximity monitoring by mimicking direct visual observation from experienced viticulturists. While the latter traditionally are responsible for a set of everyday practices in the field, these are time and resource consuming. VineInspector was proven to be effective in two of these practices, performing them automatically. Therefore, it enables both the continuous monitoring and assessment of a vineyard’s phenological development in a more efficient manner, making way to more assertive and timely practices against pests and diseases.

2022

UAV-Based Hyperspectral Monitoring Using Push-Broom and Snapshot Sensors: A Multisite Assessment for Precision Viticulture Applications

Authors
Sousa, JJ; Toscano, P; Matese, A; Di Gennaro, SF; Berton, A; Gatti, M; Poni, S; Padua, L; Hruska, J; Morais, R; Peres, E;

Publication
SENSORS

Abstract
Hyperspectral aerial imagery is becoming increasingly available due to both technology evolution and a somewhat affordable price tag. However, selecting a proper UAV + hyperspectral sensor combo to use in specific contexts is still challenging and lacks proper documental support. While selecting an UAV is more straightforward as it mostly relates with sensor compatibility, autonomy, reliability and cost, a hyperspectral sensor has much more to be considered. This note provides an assessment of two hyperspectral sensors (push-broom and snapshot) regarding practicality and suitability, within a precision viticulture context. The aim is to provide researchers, agronomists, winegrowers and UAV pilots with dependable data collection protocols and methods, enabling them to achieve faster processing techniques and helping to integrate multiple data sources. Furthermore, both the benefits and drawbacks of using each technology within a precision viticulture context are also highlighted. Hyperspectral sensors, UAVs, flight operations, and the processing methodology for each imaging type’ datasets are presented through a qualitative and quantitative analysis. For this purpose, four vineyards in two countries were selected as case studies. This supports the extrapolation of both advantages and issues related with the two types of hyperspectral sensors used, in different contexts. Sensors’ performance was compared through the evaluation of field operations complexity, processing time and qualitative accuracy of the results, namely the quality of the generated hyperspectral mosaics. The results shown an overall excellent geometrical quality, with no distortions or overlapping faults for both technologies, using the proposed mosaicking process and reconstruction. By resorting to the multi-site assessment, the qualitative and quantitative exchange of information throughout the UAV hyperspectral community is facilitated. In addition, all the major benefits and drawbacks of each hyperspectral sensor regarding its operation and data features are identified. Lastly, the operational complexity in the context of precision agriculture is also presented.

2022

Modeling Stand-Alone Photovoltaic Systems with Matlab/Simulink

Authors
Baptista, J; Pimenta, N; Morais, R; Pinto, T;

Publication
PROGRESS IN ARTIFICIAL INTELLIGENCE, EPIA 2022

Abstract

2022

Segmentation as a Preprocessing Tool for Automatic Grapevine Classification

Authors
Carneiro, GA; Pádua, L; Peres, E; Morais, R; de Sousa, JJM; Cunha, A;

Publication
IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2022, Kuala Lumpur, Malaysia, July 17-22, 2022

Abstract

Supervised
thesis

2021

Estimulação e sensoriamento da interface de implantes ósseos ativos instrumentados

Author
Nuno Miguel dos Santos Pinto da Silva

Institution
UTAD

2021

Automatic detection of earthquake's deformations in SAR interferograms

Author
Bruno Miguel Ferreira Silva

Institution

2019

Estimulação e sensoriamento da interface de implantes ósseos ativos instrumentados

Author
Nuno Miguel dos Santos Pinto da Silva

Institution
UTAD

2019

Desenvolvimento de uma aplicação androoide para o jardim botânico da Utad

Author
João Carlos Trindade Moreira

Institution
UTAD

2019

Técnicas avançadas de monitorização em aplicações de agricultura de precisão

Author
Jorge Miguel Ferreira da Silva Mendes

Institution
UTAD