Percorrer por autor "Alcantara, Carlos Boduar"
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- Artificial intelligence-based user interaction module for autonomous mobile service robotsPublication . Alcantara, Carlos Boduar; Oliveira Júnior, Alexandre de; Costa, Julio; Ricken, Lucas; Mendes, Andre C.; Leitão, PauloWith the evolution of Artificial Intelligence (AI) technologies, there is a growing demand for Intelligent Personal Assistants (IPAs) that allow fluid communication with humans. However, there are still several challenges to overcome, such as difficulty in understanding nuances in some contexts. Therefore, this study seeks to mitigate these gaps by presenting a modular and scalable architecture for integrating IPAs into autonomous service robots. The architecture allows communication between various robot systems and peripherals with AI mechanisms, including Large Language Model (LLM) and Natural Language Processing, which seek to improve the user experience. The proposed architecture was applied to developing a service robot designed to guide and interact with people in a university environment, incorporating the RASA framework with an LLM for natural language processing and response generation. The paper discusses the adopted technologies, the current state of development, the difficulties encountered, and the analysis of the first feedback from volunteers.
- Sustainably enhancing olive oil production: intelligent system architecturePublication . Alcantara, Carlos Boduar; Jorge, Luísa; Vaz, Clara B.Olive oil production is a noteworthy economic activity in multiple places worldwide. Due to environmental degradation and lack of resources with population growth, there is a global tendency for more sustainable and efficient practices, driving the implementation of more responsible agricultural and industrial systems. This paper aims to develop an intelligent system architecture focused on optimizing the production of olive oil, improving product quality, reducing operational waste, and maximizing the efficient use of natural resources. Through the use of Industrial Internet of Things (IIoT) technologies, the proposed solution aims to monitor and control the parameters of olive oil production automatically. In addition, the study addresses sensors already used in the market and existing systems to compare and seek improvements. The proposed architecture contains three layers: device, edge, and cloud computing layer, which are integrated and enable the implementation of a scalable and complete solution that allows real-time visualization and control of the production process.