Tiago Oliveira, a student from the Faculty of Sciences and Technology of the University of Coimbra (FCTUC) was distinguished with the "ABB Award", by the multinational Asea Brown Boveri (ABB), for his study in the field of high-reliability electrical energy supply systems, developed within his MSc thesis, entitled "Model Predictive Control of Parallel Connected Power Supplies". The award ceremony was held in the Council Room of the FCTUC central building, at pole II of the University of Coimbra, on January 17.
Tiago´s thesis, for which he obtained the final classification of 19 values, was hosted by IT in Coimbra, developed in the Power Systems group under the supervision of André Mendes (IT/FCTUC) and Luís Caseiro (IT). Specifically, Tiago has developed innovative control algorithms for uninterruptible power supply (UPS), connected in parallel.
UPS systems "allow supplying electrical charges in good condition, even when severe disturbance or interruptions occur in the supply of electrical power", explains André Mendes. The algorithms developed by Tiago Oliveira “allow to control the individual power that each UPS system provides to the charge, thus enabling greater system reliability and performance», adds André Mendes.
Tiago´s thesis was framed within the project DRIFT - “Datacenter Resilience Increase through Fault Tolerance in UPS systems”, under development at the Power Systems group of IT in Coimbra.
The “ABB Award” annually distinguishes students from FCTUC Master´s in Electrical who has obtained the highest classification in a MSc thesis developed within the areas of actioning / speed variation or power transformers. The prize, in the amount of one thousand euros, also includes a paid internship at the company.
The Mobile Health project was created to monitor people's health, without any specific action to do so. The monitoring devices should be incorporated in daily use objects, without modifying its appearance or functionality, the data produced should be available for instant or aggregated analysis.
As a proof of concept, a chair capable of approximately measure a person’s weight was developed. To do that, a set of piezoresistive sensors was placed under the seat, as well as the processing and communication units. The raw data can be transmitted directly to a personal device (e.g. smartphone, smartwatch, etc.) using Bluetooth, or can be transmitted through Wi-Fi to the cloud. Depending on the person’s desire, this information can also be available to the medical entities, enabling the possibility of constant tracking and advice. More than that, if permission is conceded, machine learning algorithms can relate the obtained results with other parameters to understand possible relations between different behaviors.
The idea of developing a weighting chair emerged from the difficulty that many people feel in stepping on a traditional scale. This problem is especially important in patients with diseases such as obesity or anorexia, in some cases the social pressure is so high that people refuse to do it.
To developed this project, it was necessary to put together a multidisciplinary team. Felisberto Pereira (PhD students), Ricardo Torres (MSc students), Ricardo Correia (Researcher) and Nuno B. Carvalho (Professor) from Radio Systems – IT Aveiro, are working in the monitoring and communication aspects; Filipe Reis(MSc students), and Samuel Silva (Researcher) from IEETA, are developing the mobile application and machine learning algorithms; Sandra Soares (Professor), and Tiago Santos (Doctor) are taking care of data analysis and patients tests.