2025
Authors
Faber, A; Torres, Â; Boucher, E; Ljungkvist, F; Hauspie, L; Spaas, S; Duarte, J; Malheiro, B; Ribeiro, C; Justo, J; Silva, F; Ferreira, P; Guedes, P;
Publication
Lecture Notes in Educational Technology
Abstract
In the spring of 2023, a team of European Project Semester (EPS) students enrolled at the Instituto Superior de Engenharia do Porto (ISEP) chose to foster socialisation in urban spaces. Public spaces are ideal sites to promote social interaction and community involvement. The aim of this project is then to use such places to divert attention from smartphones by promoting physical social interaction. In recent years, the combination of interactive games and technology has emerged as a potential strategy to increase the use and allure of public areas. The proposed solution, named Shift it, is a puzzle game that combines technology with old school gaming, providing a fun and unique socialising experience. The game, to be installed in public areas, has as key features inclusiveness (invites all people to play), fun (creates a healthy competitive setup) and empathy (creates puzzles by taking and scrambling user pictures). This paper presents the proposed design, which was based on state-of-the-art, ethics, market and sustainability analyses, followed by the development and testing of a proof-of-concept prototype. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.
2024
Authors
Youssef, ESE; Tokhi, MO; Silva, MF; Rincon, LM;
Publication
Lecture Notes in Networks and Systems
Abstract
2023
Authors
Tardioli, D; Matellán, V; Heredia, G; Silva, MF; Marques, L;
Publication
Lecture Notes in Networks and Systems
Abstract
2023
Authors
Tardioli, D; Matellán, V; Heredia, G; Silva, MF; Marques, L;
Publication
Lecture Notes in Networks and Systems
Abstract
2021
Authors
Manuel Silva;
Publication
Journal of Artificial Intelligence and Technology
Abstract
2025
Authors
Tinoco, V; Silva, MF; dos Santos, FN; Morais, R;
Publication
SENSORS
Abstract
Agriculture needs to produce more with fewer resources to satisfy the world's demands. Labor shortages, especially during harvest seasons, emphasize the need for agricultural automation. However, the high cost of commercially available robotic manipulators, ranging from EUR 3000 to EUR 500,000, is a significant barrier. This research addresses the challenges posed by low-cost manipulators, such as inaccuracy, limited sensor feedback, and dynamic uncertainties. Three control strategies for a low-cost agricultural SCARA manipulator were developed and benchmarked: a Sliding Mode Controller (SMC), a Reinforcement Learning (RL) Controller, and a novel Proportional-Integral (PI) controller with a self-tuning feedforward element (PIFF). The results show the best response time was obtained using the SMC, but with joint movement jitter. The RL controller showed sudden breaks and overshot upon reaching the setpoint. Finally, the PIFF controller showed the smoothest reference tracking but was more susceptible to changes in system dynamics.
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