58 documents found, page 1 of 6
Intelligent sports weights
Duarte, Olga dos Santos; Jacinto, Gustavo; Véstias, Mário; Véstias, Mário; Duarte, Rui Policarpo; Duarte, RuiWeightlifting is a common fitness activity and can be practiced individually without supervision. However, performing regular weightlifting exercises without any form of feedback can lead to serious injuries. To counter this, this work proposes a different approach to automatic weightlifting supervision off-the-person. The proposed embedded system is coupled to the weights and evaluates if they follow the corre...
Intelligent traffic control strategies for VLC-connected vehicles and pedestria...
Galvão, Gonçalo; Vieira, Manuela; Vieira, Manuel Augusto; Véstias, Mário; Louro, PaulaUrban traffic congestion leads to daily delays, driven by outdated, rigid control systems. As vehicle numbers grow, fixed-phase signals struggle to adapt to real-time conditions. This work presents a decentralized Multi-Agent Reinforcement Learning (MARL) system to manage a traffic cell composed of five intersections, introducing the novel Strategic Anti-Blocking Phase Adjustment (SAPA) module, developed to ena...
Decentralized Multi-Agent Reinforcement Learning with Visible Light Communicati...
Vieira, Manuel Augusto; Galvão, Gonçalo; Vieira, Manuela; Véstias, Mário; Louro, Paula; Vieira, PedroThe rapid growth of urban vehicle and pedestrian flows has intensified congestion, delays, and safety concerns, underscoring the need for sustainable and intelligent traffic management in modern cities. Traditional centralized traffic signal control systems often face challenges of scalability, heterogeneity of traffic patterns, and limited real-time adaptability. To address these limitations, this study propos...
Integrating Visible Light Communication and Deep Reinforcement Learning for Sma...
Galvão, Gonçalo; Vieira, Manuel A.; Vieira, Manuela; Véstias, Mário; Louro, Paula; Vieira, PedroUrban traffic management is increasingly challenged by rising vehicle and pedestrian flows, resulting in congestion, delays, and safety riskW. This article proposes an innovative traffic signal control framework that integrates Deep Reinforcement Learning (DRL) with Visible Light Communication (VLC) to optimize operations at intersections, which are critical bottlenecks in urban networks. A decentralized DRL ag...
Decentralized multi-agent reinforcement learning with visible light communicati...
Augusto Vieira, Manuel; Gonçalo Galvão; Vieira, Manuela; Véstias, Mário; Louro, Paula; Vieira, PedroThe rapid growth of urban vehicle and pedestrian flows has intensified congestion, delays, and safety concerns, underscoring the need for sustainable and intelligent traffic management in modern cities. Traditional centralized traffic signal control systems often face challenges of scalability, heterogeneity of traffic patterns, and limited real-time adaptability. To address these limitations, this study propos...
Fast and accurate system for onboard target recognition on raw SAR echo data
Jacinto, Gustavo; Véstias, Mário; Flores, Paulo; Duarte, RuiSynthetic Aperture Radar (SAR) onboard satellites provides high-resolution Earth imaging independent of weather conditions. SAR data are acquired by an aircraft or satellite and sent to a ground station to be processed. However, for novel applications requiring real-time analysis and decisions, onboard processing is necessary to escape the limited downlink bandwidth and latency. One such application is real-tim...
Intelligent Intersection Management through Multi-agent Reinforcement Learning,...
Vieira, Manuel A.; Antunes, Tomás; Galvão, Gonçalo; Vieira, Manuela; Véstias, Mário; Louro, PaulaUrban traffic management faces growing challenges due to increasing volumes of vehicles and pedestrians, resulting in congestion, delays, and safety concerns. This study introduces an innovative traffic signal control framework that integrates Multi-Agent Reinforcement Learning (MARL) with Visible Light Communication (VLC) and a Self-Adaptive Phase Adjustment (SAPA) module to enhance coordination across urban i...
Síntese de alto nível em FPGA
Véstias, Mário; Flores, Paulo; Cláudio de Campos Neto, HorácioAs metodologias e as ferramentas de projeto de sistemas digitais têm evoluído com o objetivo de conseguir circuitos melhores e mais eficientes. Com o aumento da complexidade dos sistemas digitais, surgiu uma nova dimensão no desenvolvimento destes sistemas relacionada com a eficiência de projeto. É necessário lidar com o aumento crescente da complexidade dos circuitos, com a redução do tempo disponível para o p...
Integration of visible light communication, artificial intelligence, and rerout...
Vieira, Manuela; Galvão, Gonçalo; Vieira, Manuel Augusto; Véstias, Mário; Vieira, Pedro; Louro, PaulaThis study combines Visible Light Communication (VLC) and Artificial Intelligence (AI) to enhance traffic signal control, reduce congestion, and improve safety, through real-time monitoring and dynamic traffic management. Leveraging VLC technology, the system uses existing road infrastructure to transmit live data on vehicle and pedestrian positions, speeds, and queues. AI agents, employing Deep Reinforcement L...
Energy-efficient and real-time wearable for wellbeing-monitoring IoT system bas...
Frutuoso, Maria Inês; Cláudio de Campos Neto, Horácio; Véstias, Mário; Duarte, Rui PolicarpoWearable devices used for personal monitoring applications have been improved over the last decades. However, these devices are limited in terms of size, processing capability and power consumption. This paper proposes an efficient hardware/software embedded system for monitoring bio-signals in real time, including a heart rate calculator using PPG and an emotion classifier from EEG. The system is suitable for ...