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About

About

PhD by the Faculty of Engineering of the University of Porto in February 2004, after presentation and discussion of the thesis "Dynamic Test of Analog / Digital Converters - New Methods of Calculation of Functional Characterization Parameters".

Assistant Professor of the Department of Electrotechnical and Computer Engineering of the Faculty of Engineering of the University of Porto (DEEC-FEUP) where he teaches curricular units in the areas of Electronics and Microprocessors.

He is an INESC TEC researcher and coordinator at CRIIS (Center of Industrial Robotics and Intelligent Systems) where he participates in several scientific projects.

His skills and interests include Industrial Robotics, Automation and Control Systems, Industrial Networks, Embedded Systems, Industry 4.0 and Internet of Things.

Interest
Topics
Details

Details

007
Publications

2022

Gerber File Parsing for Conversion to Bitmap Image–The VINCI7D Case Study

Authors
Sousa, RB; Rocha, C; Mendonca, HS; Moreira, AP; Silva, MF;

Publication
IEEE ACCESS

Abstract

2020

Pneuma: entrepreneurial science in the fight against the COVID-19 pandemic - a tale of industrialisation and international cooperation

Authors
Mendonça J.M.; Cruz N.; Vasconcelos D.; Sá-Couto C.; Moreira A.P.; Costa P.; Mendonça H.; Pereira A.; Naimi Z.; Miranda V.;

Publication
Journal of Innovation Management

Abstract
When the COVID-19 pandemic hits Portugal in early March 2020, medical doctors, engineers and researchers, with the encouragement of the Northern Region Health Administration, teamed up to develop and build, locally and in a short time, a ventilator that might eventually be used in extreme emergency situations in the hospitals of northern Portugal. This letter tells you the story of Pneuma, a low-cost emergency ventilator designed and built under harsh isolation constraints, that gave birth to derivative designs in Brazil and Morocco, has been industrialized with 200 units being produced and is now looking forward to the certification as a medical device that will possibly support a go-to-market launch. Open intellectual property (IP), multidisciplinarity teamwork, fast prototyping and product engineering have shortened to a few months an otherwise quite longer idea-to-product route, clearly demonstrating that when scientific and engineering knowledge hold hands great challenges can be successfully faced.

2019

Parallelization of a Vine Trunk Detection Algorithm for a Real Time Robot Localization System

Authors
Azevedo, F; Shinde, P; Santos, L; Mendes, J; Santos, FN; Mendonca, H;

Publication
2019 19TH IEEE INTERNATIONAL CONFERENCE ON AUTONOMOUS ROBOT SYSTEMS AND COMPETITIONS (ICARSC 2019)

Abstract
Developing ground robots for crop monitoring and harvesting in steep slope vineyards is a complex challenge due to two main reasons: harsh condition of the terrain and unstable localization accuracy obtained with Global Navigation Satellite System (GNSS). In this context, a reliable localization system requires an accurate detector for high density of natural/artificial features. In previous works, we presented a novel visual detector for Vineyards Trunks and Masts (ViTruDe) with high levels of detection accuracy. However, its implementation on the most common processing units - central processing units (CPU), using a standard programming language (C/C++), is unable to reach the processing efficiency requirements for real time operation. In this work, we explored parallelization capabilities of processing units, such as graphics processing units (GPU), in order to accelerate the processing time of ViTruDe. This work gives a general perspective on how to parallelize a generic problem in a GPU based solution, while exploring its efficiency when applied to the problem at hands. The ViTruDe detector for GPU was developed considering the constraints of a cost-effective robot to carry-out crop monitoring tasks in steep slope vineyard environments. We compared the proposed ViTruDe implementation on GPU using Compute Unified Compute Unified Device Architecture(CUDA) and CPU, and the achieved solution is over eighty times faster than its CPU counterpart. The training and test data are made public for future research work. This approach is a contribution for an accurate and reliable localization system that is GNSS-free. © 2019 IEEE.

2019

System-level study on impulse-radio integration-and-fire (IRIF) transceiver

Authors
Kianpour, I; Hussain, B; Mendonca, HS; Tavares, VG;

Publication
AEU-INTERNATIONAL JOURNAL OF ELECTRONICS AND COMMUNICATIONS

Abstract
Integrate-and-fire (IFN) model of a biological neuron is an amplitude-to-time conversion technique that encodes information in the time-spacing between action potentials (spikes). In principle, this encoding scheme can be used to modulate signals in an impulse radio ultra wide-band (IR-UWB) transmitter, making it suitable for low-power applications, such as in wireless sensor networks (WSN) and biomedical monitoring. This paper then proposes an architecture based on IFN encoding method applied to a UWB transceiver scenario, referred to herein as impulse-radio integrate-and-fire (IRIF) transceiver, followed by a system-level study to attest its effectiveness. The transmitter is composed of an integrate-and-fire modulator, a digital controller and memory block, followed by a UWB pulse generator and filter. At the receiver side, a low-noise amplifier, a squarer, a low-pass filter and a comparator form an energy-detection receiver. A processor reconstructs the original signal at the receiver, and the quality of the synthesized signal is then verified in terms of effective number of bits (ENOB). Finally, a link budget is performed. (C) 2019 Published by Elsevier GmbH.

2019

Multi-Protocol LoRaWAN/Wi-Fi Sensor Node Performance Assessment for Industry 4.0 Energy Monitoring

Authors
Ferreira, P; Miranda, RN; Cruz, PM; Mendonca, HS;

Publication
Proceedings of the 2019 9th IEEE-APS Topical Conference on Antennas and Propagation in Wireless Communications, APWC 2019

Abstract
This paper describes the implementation of an end-to-end Internet of Things (IoT) solution, focusing specifically in the multi-protocol sensor node with LoRaWAN and Wi-Fi connectivity options (Pycom's FiPy). A performance assessment will be presented, addressing a comparison between the different protocols (LoRaWAN vs. Wi-Fi) in terms radio coverage, timing issues, among others. Further, it will be investigated the integration onto the sensor node of sensor/actuator circuit blocks for energy metering, supported on Microchip's ATM90E26 single-phase meter. This will provide a practical use case in the field of Industry 4.0, leading to preliminary insights for power quality monitoring. © 2019 IEEE.

Supervised
thesis

2022

Edge AI for Image Analysis and Defect Detection

Author
Diogo Afonso Correia Remião

Institution
UP-FEUP

2022

Otimização do Desempenho de Redes Neuronais em Sistemas Embarcados

Author
João António de Brito Ferreira Gonçalves

Institution
UP-FEUP

2021

Infrastructure Management Tool

Author
Francisco Fernandes Machado

Institution
UP-FEUP

2021

Sistema de Deteção de Incêndio Adaptável

Author
José Ricardo Silva e Sousa

Institution
UP-FEUP

2021

Web Application for Supervising and Managing an Automatic Cross-Docking System

Author
Francisco Rego Moreira da Silva Costa

Institution
UP-FEUP