TinyML for Safe Driving: The Use of Embedded Machine Learning for Detecting Driver Distraction. - Thommas K. S. Flores; Marianne Silva; Mariana Azevedo; Thaís Medeiros; Morsinaldo Medeiros; Ivanovitch Silva; Max Mauro Dias Santos; Daniel G. Costa (MetroAutomotive, 2023)

An Adaptive TinyML Unsupervised Online Learning Algorithm for Driver Behavior Analysis. - Marianne Silva; Thaís Medeiros; Mariana Azevedo; Morsinaldo Medeiros; Mikael Themoteo; Tatiane Gois; Ivanovitch Silva; Daniel G. Costa (MetroAutomotive, 2023)

Leveraging IoT and TinyML for Smart Battery Management in Electric Bicycles. - Thommas K. S. Flores; Matheus Andrade; Morsinaldo Medeiros; Miguel Amaral; Marianne Silva; Ivanovitch Silva (SIoT, 2023)

A Framework for Efficient Communication in IoT Applications in the Automotive Industry with OBD-II Edge. - Morsinaldo Medeiros; Mariana Azevedo; Miguel Amaral; Carlos M. D. Viegas; Marianne Silva; Ivanovitch Silva; Daniel G. Costa (SIoT, 2023)

A Framework to Support Collection, Processing and Analysis of Smart Vehicles Data. - Mariana Azevedo; Thaís Medeiros; Morsinaldo Medeiros; Carlos M. D. Viegas; Marianne Silva; Ivanovitch Silva; Daniel G. Costa (WF-IoT, 2023)

A Multi-Layered Methodology for Driver Behavior Analysis Using TinyML and Edge Computing. - Morsinaldo Medeiros; Thommas K. S. Flores; Marianne Silva; Ivanovitch Silva (EAIS, 2024)

Optimizing Vehicle IoT Systems: SUMO-Digital Twin Performance Analysis. - Mariana Azevedo; Matheus Andrade; Morsinaldo Medeiros; Thaís Medeiros; Marianne Silva; Ivanovitch Silva; Emiliano Sisinni; Paolo Ferrari (MetroInd4.0 & IoT, 2024)

TinyML Implementation and Optimization for Fuel Type Classification on OBD-II Edge Device. - Miguel Amaral; Morsinaldo Medeiros; Matheus Andrade; Thommas K. S. Flores; Marianne Silva; Ivanovitch Silva (SIoT, 2024)

Enhanced Vector Quantization for Embedded Machine Learning: A Post-Training Approach With Incremental Clustering. - Thommas K. S. Flores; Morsinaldo Medeiros; Marianne Silva; Daniel G. Costa; Ivanovitch Silva (IEEE Access, 2025)

Advancing Tiny Machine Learning Operations: Robust Model Updates in the Internet of Intelligent Vehicles. - Thommas K. S. Flores; Ivanovitch Silva; Mariana Azevedo; Thaís Medeiros; Morsinaldo Medeiros; Daniel G. Costa; Paolo Ferrari; Emiliano Sisinni (IEEE Micro, 2025)

TEDA-forecasting: an unsupervised tinyML incremental learning approach for outlier processing and forecasting. - Pedro Andrade; Morsinaldo Medeiros; Marianne Silva; Daniel G. Costa; Ivanovitch Silva (Computing, 2025)