Rui Duarte

Automatic Camera Calibration Using a Single Image to extract Intrinsic and Extrinsic Parameters

Carlos A. Cunha, José C. Cardoso, R. P. D. . (2024).
Automatic Camera Calibration Using a Single Image to extract Intrinsic and Extrinsic Parameters.
International Journal of Intelligent Systems and Applications in Engineering, 12(3), 1766–1778.
Retrieved from https://ijisae.org/index.php/IJISAE/article/view/5586

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PIDI/CISeD/2023/013 • Práticas de Mobilidade Sustentável

Principal Researcher:
Eduardo Miguel Teixeira Mendonça Gouveia
Duration: 2023 – 2025

Cised team members
Filipe Manuel Simões Caldeira
Vasco Eduardo Graça Santos
Maria Elisabete Ferreira Silva
José Luis Mendes Loureiro Abrantes
Paulo Joaquim Antunes Vaz

The dynamics imposed on the electric mobility market and environmental and technological issues lead to a paradigm involving various energy chain agents, from producers, consumers, traders, and network operators.
From the outset, private users and entities are faced with various mobility solutions, including vehicles with a thermal engine, hybrid, or purely electric. In the case of EV (Electric Vehicles), decision-making includes choices that are covered with different levels of sophistication, from charging an electric vehicle from a simple single-phase 16 A socket to more complex solutions that fit the assembly of Wallbox.
Other variables, such as the type of charging (fast/slow) and battery life, are also important. The most appropriate tariff option for each case and the maintenance inherent to each type of mobility solution make the decision denser.
Concerning energy production (self-consumption) and considering the user profile, it will be essential to reflect on mobility solutions that think of renewable energy production (solar photovoltaic, other) in which the EV can be a storage point for that energy with the consequent assessment of the potential economic benefit and the resultant minimization of the ecological footprint, highlighting the carbon footprint.
On the other hand, all these dynamics of sustainable mobility will impact the electrical grids. The network operator will now have to deal with these “new” realities, minimizing the impact on the network, namely in terms of power flow and in terms of the quality of the voltage wave. Also, at the end customer level, there are reports of situations in which inverters “withdraw” photovoltaic production from the grid in the face of disturbances in the quality of the voltage wave. These situations must be assessed at the level of the network operator when they have external causes at their origin or at the level of the consumer when the source of the disturbance is internal.
The present project proposal intends to contribute at several levels in several agents: users, energy producers (self-consumption), network operators, general public due to possible ascertainable environmental benefits.
The intended results include the guidance of dissertations, digital platforms, and publication in scientific journals and communications. Protocols for the study of sustainable mobility solutions within the scope of local agents may also be framed. In terms of results, it will also be essential to organize dissemination activities to disseminate the results obtained within the community and improve the visibility of research and development work in the mobility and transport sector.

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C644867037-00000013-8/8 • GA_OBTURADORES GREENAUTO: Automated automotive body parts mounting system

Principal Researcher:
Serafim Oliveira

Duration: 2023 – 2025

Cised team members
José Luís Silva
Daniel Albuquerque
Rui Pedro Duarte
Olga Contente

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Many currently available robotic systems have important limitations regarding adaptation to car electrification trends. To overcome these limitations, this project focuses on developing one efficient piece of equipment for shutter assembly, exploring the potential of artificial vision technology. It includes simulation studies to assess the viability of the proposed solution, which will be prototyped and tested in laboratory and pre-industrial conditions afterward.

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PIDI/CISeD/2023/012 • Computer vision in unmanned aerial vehicle (UAV) for industrial applications

Principal Researcher:
José Luís Henriques da Silva
Duration: 2023 – 2025

Cised team members
Serafim Oliveira
Rui Pedro Duarte
José Luís Abrantes
Paulo Vaz
João Menoita

Unmanned Aerial Vehicles (UAVs) can be used to monitor activities and offer technological solutions in various industrial sectors.
Applying machine vision algorithms to UAVs allows vehicles to understand and interact with the surrounding environment more intelligently. They can identify and avoid obstacles, make navigation decisions based on the collected visual information, and even perform complex tasks such as following predetermined routes or recognizing specific objects.
However, artificial vision has challenges such as the need to deal with changing lighting conditions, changing weather conditions and the presence of complex and moving objects. Machine vision algorithms need to be robust enough to handle these situations and provide accurate and reliable results.
Furthermore, it is important to perform rigorous validation and testing of machine vision algorithms under different scenarios and conditions to ensure that they are robust enough before being deployed in practical applications.
This project intends to implement this technology in industrial environments, namely in precision positioning (Vision Positioning System – VPS) and automated inspection.
The use of UAVs equipped with VPS and automated inspection systems allows real-time monitoring of various industrial activities, such as detecting chemical leaks, identifying risk areas, monitoring production flow, visual quality control, among others.
Data collected by UAVs or sensors can be processed in real time and provide valuable information for decision making and ensuring safety and compliance in industrial environments.

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Agile-based Requirements Engineering for Machine Learning: A Case Study on Personalized Nutrition

Cunha, C., Oliveira, R., & Duarte, R. (2023).
Agile-based Requirements Engineering for Machine Learning: A Case Study on Personalized Nutrition.
International Journal of Intelligent Systems and Applications in Engineering, 12(2), 319–327.
Retrieved from https://ijisae.org/index.php/IJISAE/article/view/4255

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