Seminário – Mesa Redonda Taxa de Juros O Óbvio e Não Óbvio
july 5, 2023 | 19.30 horas | Sala 6 – Escola Superior de Tecnologia e Gestão de Viseu
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
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.
Combining K-Means and XGBoost Models for Anomaly Detection Using Log Datasets
Henriques, J., Caldeira, F., Cruz, T., Simões, P. (2023).
Combining K-Means and XGBoost Models for Anomaly Detection Using Log Datasets.
In Víctor A. V. (Ed.), Advanced Cybersecurity Services Design (pp. 57-72).
Switzerland: MDPI.
doi:10.3390/electronics9071164
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.
PIDI/CISeD/2023/010 • SafeSec-M-Audit – Estrutura de Monitorização e Auditoria de Segurança e Saúde no Trabalho
Principal Researcher:
Filipe Manuel Simões Caldeira
Duration: 2023 – 2025
Cised team members
João Pedro Menoita Henriques
The Civil Construction industry is characterized by involving projects of high complexity, dimension and budgets with the use of numerous human resources.
However, its construction sites are environments conducive to the occurrence of accidents, some of them fatal or with serious injuries, as a result of the number of workers, goods and equipment that circulate and operate in them. Falls are one of the most recurrent causes associated with accidents. Other consequences of accidents stem from the costs resulting from compensation and new hires, legal liabilities and delays in work, in addition to the impact on the reputation of organizations.
Although there is a national legal framework for managing health and safety at work, with its concepts and standards, the mandatory use of PPE (personal protective equipment), it appears that there is a strong rejection on the part of workers regarding its use. Some of the problems are mitigated by safety management professionals, through the identification of occupational risks on the site, training in the use and handling of PPE, as well as raising awareness of safe behaviour. However, these are disconnected from the reality of operations at the construction site.
To overcome this reality, this project proposes a structure (framework) for auditing safety and health at work in order to reduce the number of accidents at work. This project also intends to define a model that aims to identify the best distribution of sensors across the work sites, avoiding accidents and minimizing their response time. Given the large volume and speed of data to be collected for real-time monitoring processes, an aggregator hub of messages will be proposed that allows efficient exchange between the various stakeholders. Efforts will be delivered to enhance its scalability and reliability by defining a set of performance indicators (KPIs) to guarantee the quality of the services provided by the framework in an uninterrupted manner and with fast response times when faced with large loads.
Modelling sorption processes of 10-h dead Pinus pinaster branches
Lopes, S., Santos, S., Rodrigues, N., Pinho, P., Viegas, D. (2023).
Modelling sorption processes of 10-h dead Pinus pinaster branches.
International Journal of Wildland Fire, 32(6), 903-912.
https://doi.org/10.1071/WF22127
Preparing students for the software industry new demands
Metrolho, J., Ribeiro, F., Batista, R., Graça, P., Pacheco, D. (2023).
Preparing students for the software industry new demands.
International Journal on Advances in Software, 16(1-2), 71-81.
Underage citizens monitoring applications – A review of the state of the art and guidelines for future implementations
Chappara, M., Ribeiro, F., & Metrôlho, J. (2023).
Underage citizens monitoring applications – A review of the state of the art and guidelines for future implementations.
International Journal of Engineering Science Technologies, 7(4), 1–18.
https://doi.org/10.29121/ijoest.v7.i4.2023.524
Algorithms and Models for Automatic Detection and Classification of Diseases and Pests in Agricultural Crops: A Systematic Review
Francisco, M., Ribeiro, F., Metrôlho, J., Dionísio, R. (2023).
Algorithms and Models for Automatic Detection and Classification of Diseases and Pests in Agricultural Crops: A Systematic Review.
Applied Sciences, 13(8), 4720.
https://doi.org/10.3390/app13084720
Pressure-Based Posture Classification Methods and Algorithms: A Systematic Review
Fonseca, L., Ribeiro, F., Metrôlho, J. (2023).
Pressure-Based Posture Classification Methods and Algorithms: A Systematic Review.
Computers, 12(5), 104.
https://doi.org/10.3390/computers12050104