A Novel Methodology for the Characterization of Cutting Conditions in Turning Processes Using Machine Learning Models and Acoustic Emission Signals. - Telmo Fernández de Barrena; Juan Luis Ferrando; Ander García; Pedro José Arrazola; José Manuel Abete; Diego Herrero (SOCO, 2021)

A Novel Machine Learning-Based Methodology for Tool Wear Prediction Using Acoustic Emission Signals. - Juan Luis Ferrando Chacón; Telmo Fernández de Barrena; Ander García; Mikel Sáez de Sáez de Buruaga; Xabier Badiola; Javier Vicente (Sensors, 2021)

5G and MEC Based Data Streaming Architecture for Industrial AI. - Telmo Fernández de Barrena Sarasola; Juan Luis Ferrando Chacón; Ander García; Michail Dalgitsis (IN4PL, 2023)

Edge Architecture for the Integration of Soft Models Based Industrial AI Control into Industry 4.0 Cyber-Physical Systems. - Ander García; Telmo Fernández de Barrena; Juan Luis Ferrando Chacón; Xabier Oregui; Zelmar Etxegoien (SOCO (2), 2023)

Containerized Edge Architecture for Centralized Industry 4.0 Fleet Management. - Ander García; Javier Tardos; Juan Luis Ferrando; Telmo Fernández de Barrena (WF-IoT, 2023)

Impact of Real-Time Linux for Industrial Edge AI. - Telmo Fernández de Barrena; Ander García; Javier Franco; Juan Luis Ferrando (IN4PL (2), 2024)

IIoT Protocols for Edge/Fog and Cloud Computing in Industrial AI: A High Frequency Perspective. - Telmo Fernández de Barrena Sarasola; Ander García; Juan Luis Ferrando (Int. J. Cloud Appl. Comput., 2024)

Adaptive high frequency data streaming for Soft Real-Time Industrial AI: A scalable microservices based architecture with dynamic downsampling. - Telmo Fernández de Barrena; Alcides Fernandes; Juan Luis Ferrando; Ander García; Hugo Landaluce; Ignacio Angulo (Array, 2025)