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Article published in international journal Sensors (MDPI)

NOVEMBER 28, 2020

On November, 28 of 2020, an article authored by Maria João Sousa, Alexandra Moutinho and Miguel Almeida [1], was published in a peer-reviewed international journal, namely Sensors from the Multidisciplinary Digital Publishing Institute (MDPI).

The article presents analyses of the sensing capabilities and the image processing pipelines of thermal imaging sensors for fire detection applications, paving the way for the development of autonomous systems for early warning and monitoring of fire events.

The article is available online, published under an open-access licence (https://www.mdpi.com/1424-8220/20/23/6803).

Reference:
[1] M.J. Sousa, A. Moutinho and M. Almeida, “Thermal Infrared Sensing for Near Real-Time Data-Driven Fire Detection and Monitoring Systems”, Sensors, 2020, 20(23):6803. doi: 10.3390/s20236803

Master thesis in the context of the Eye in the Sky project

October 13, 2020

In October 2020, Vasco Cepêda completed his master’s degree in Mechanical Engineering presenting his work entitled “Simulation of a latex balloon with a hydrogen generation system”.

This work was supervised by professors Alexandra Moutinho and Rui Costa Neto, being developed in the context of the Eye in the Sky Project.

Reference:
[1] V. Cepêda (2020). “Simulation of a latex balloon with a hydrogen generation system”. Thesis to obtain the Master of Science Degree in Mechanical Engineering, in Instituto Superior Técnico from the University of Lisbon. Available at: https://fenix.tecnico.ulisboa.pt/cursos/memec/dissertacao/1409728525632951

Presentation of scientific article in international conference

AUGUST 27, 2020

On July, 22 of 2020, an article authored by Maria João Sousa, Alexandra Moutinho and Miguel Almeida [1], was presented at the World Congress on Computational Intelligence (WCCI), a flagship biennial international conference that joins conferences of the three branches of computational intelligence, namely: fuzzy systems (FUZZ-IEEE), neural networks (IJCNN) and evolutionary computation (CEC).

The article proposes a data-driven optimization solution for the dimensioning and design of configurations of fleets of unmanned aerial vehicles, based on an estimated demand for the need to perform aerial missions in a given region. The case study analyzed focuses on the application of this method for situations of monitoring of forest fires.

The article is available online, published under an open-access licence (https://ieeexplore.ieee.org/document/9177642), and also available on this page.

Reference:
[1] M.J. Sousa, A. Moutinho and M. Almeida. (2020). “Decentralized Distribution of UAV Fleets Based on Fuzzy Clustering for Demand-driven Aerial Services” in IEEE International Conference on Fuzzy Systems (FUZZ–IEEE), Glasgow, United Kingdom, 2020, pp.1–8, doi: 10.1109/FUZZ48607.2020.9177642.

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