lambda -CoAP: An Internet of Things and Cloud Computing Integration Based on the Lambda Architecture and CoAP. - Manuel Díaz; Cristian Martín 002; Bartolomé Rubio (CollaborateCom, 2015)

State-of-the-art, challenges, and open issues in the integration of Internet of things and cloud computing. - Manuel Díaz; Cristian Martín 002; Bartolomé Rubio (J. Netw. Comput. Appl., 2016)

SocICoAP: Social Interaction with Supplementary Sensors and Actuators through CoAP in Smartphones. - Cristian Martín 002; Jaime Chen; Manuel Diaz; Ana Reyna; Bartolomé Rubio (COMPSAC (2), 2017)

Run-time deployment and management of CoAP resources for the Internet of Things. - Cristian Martín 002; Manuel Díaz; Bartolomé Rubio (Int. J. Distributed Sens. Networks, 2017)

An Edge Computing Architecture in the Internet of Things. - Cristian Martín 002; Manuel Díaz; Bartolomé Rubio (ISORC, 2018)

On blockchain and its integration with IoT. Challenges and opportunities. - Ana Reyna; Cristian Martín 002; Jaime Chen; Enrique Soler; Manuel Díaz (Future Gener. Comput. Syst., 2018)

Smart Winery: A Real-Time Monitoring System for Structural Health and Ullage in Fino Style Wine Casks. - Eduardo Cañete; Jaime Chen; Cristian Martín 002; Bartolomé Rubio (Sensors, 2018)

Appdaptivity: An Internet of Things Device-Decoupled System for Portable Applications in Changing Contexts. - Cristian Martín 002; Jeroen Hoebeke; Jen Rossey; Manuel Díaz; Bartolomé Rubio; Floris Van Den Abeele (Sensors, 2018)

From the Edge to the Cloud: Enabling Reliable IoT Applications. - Cristian Martín 002; Daniel Garrido; Manuel Díaz; Bartolomé Rubio (FiCloud, 2019)

FogPi: A Portable Fog Infrastructure through Raspberry Pis. - Cristian Martín 002; Daniel R. Torres; Manuel Díaz; Bartolomé Rubio (MECO, 2020)

Kafka-ML: connecting the data stream with ML/AI frameworks. - Cristian Martín 002; Peter Langendörfer; Manuel Díaz; Bartolomé Rubio (CoRR, 2020)

Providing reliability and auditability to the IoT LwM2M protocol through Blockchain. - Cristian Martín 002; Iván Alba; Joaquín Trillo; Enrique Soler; Bartolomé Rubio; Manuel Díaz (CoRR, 2020)

Vibration Analysis of a Wind Turbine Gearbox for Off-cloud Health Monitoring through Neuromorphic-computing. - Pouya Soltani Zarrin; Cristian Martín 002; Peter Langendoerfer; Christian Wenger; Manuel Diaz (IECON, 2021)

Managing and Deploying Distributed and Deep Neural Models Through Kafka-ML in the Cloud-to-Things Continuum. - Alejandro Carnero; Cristian Martín 002; Daniel R. Torres; Daniel Garrido; Manuel Díaz; Bartolomé Rubio (IEEE Access, 2021)

An open source framework based on Kafka-ML for Distributed DNN inference over the Cloud-to-Things continuum. - Daniel R. Torres; Cristian Martín 002; Bartolomé Rubio; Manuel Díaz (J. Syst. Archit., 2021)

Structural health and intelligent monitoring of wind turbine blades with a motorized telescope. - Alejandro Carnero; Cristian Martín 002; Manuel Díaz (ICMLA, 2022)

UNITE: Integrated IoT-Edge-Cloud Continuum. - Marcin Brzozowski; Peter Langendoerfer; Augusto Casaca; António Grilo 001; Manuel Diaz; Cristian Martín 002; José Camacho 001; Giada Landi (WF-IoT, 2022)

Facilitating the monitoring and management of structural health in civil infrastructures with an Edge/Fog/Cloud architecture. - Cristian Martín 002; Daniel Garrido; Luis Llopis; Bartolomé Rubio; Manuel Díaz (Comput. Stand. Interfaces, 2022)

Kafka-ML: Connecting the data stream with ML/AI frameworks. - Cristian Martín 002; Peter Langendoerfer; Pouya Soltani Zarrin; Manuel Díaz; Bartolomé Rubio (Future Gener. Comput. Syst., 2022)

OpenTwins: An open-source framework for the design, development and integration of effective 3D-IoT-AI-powered digital twins. - Julia Robles; Cristian Martín 002; Manuel Díaz (CoRR, 2023)

OpenTwins: An open-source framework for the development of next-gen compositional digital twins. - Julia Robles; Cristian Martín 002; Manuel Díaz (Comput. Ind., 2023)

Federated Learning Meets Blockchain: A Kafka-ML Integration for reliable model training using data streams. - Antonio Jesús Chaves; Cristian Martín 002; Kwang Soon Kim; Adnan Shahid; Manuel Díaz (IEEE Big Data, 2024)

Distributed Federated and Incremental Learning for Electric Vehicles Model Development in Kafka-ML. - Alejandro Carnero; Omer Waqar; Cristian Martín 002; Manuel Díaz (WINCOM, 2024)

Online learning and continuous model upgrading with data streams through the Kafka-ML framework. - Alejandro Carnero; Cristian Martín 002; Gwanggil Jeon; Manuel Díaz (Future Gener. Comput. Syst., 2024)

Functions as a service for distributed deep neural network inference over the cloud-to-things continuum. - Altair Bueno; Bartolomé Rubio; Cristian Martín 002; Manuel Díaz (Softw. Pract. Exp., 2024)

Integrating FMI and ML/AI models on the open-source digital twin framework OpenTwins. - Sergio Infante; Cristian Martín 002; Julia Robles; Bartolomé Rubio; Manuel Díaz; Rafael González Perea; Pilar Montesinos; Emilio Camacho Poyato (Softw. Pract. Exp., 2024)

The orchestration of Machine Learning frameworks with data streams and GPU acceleration in Kafka-ML: A deep-learning performance comparative. - Antonio Jesús Chaves; Cristian Martín 002; Manuel Díaz (Expert Syst. J. Knowl. Eng., 2024)

Pollen recognition through an open-source web-based system: automated particle counting for aerobiological analysis. - Antonio Jesús Chaves; Cristian Martín 002; Luis Llopis; Manuel Díaz; Rocío Ruiz-Mata; Enrique de Gálvez-Montañez; Marta Recio; María del Mar Trigo; Antonio Picornell (Earth Sci. Informatics, 2024)

Towards flexible data stream collaboration: Federated Learning in Kafka-ML. - Antonio Jesús Chaves; Cristian Martín 002; Manuel Díaz (Internet Things, 2024)

Distributed digital twins on the open-source OpenTwins framework. - Sergio Infante; Julia Robles; Cristian Martín 002; Bartolomé Rubio; Manuel Díaz (Adv. Eng. Informatics, 2025)

A soft sensor open-source methodology for inexpensive monitoring of water quality: A case study of NO3- concentrations. - Antonio Jesús Chaves; Cristian Martín 002; Luis Llopis Torres; Manuel Díaz; Jaime Fernández-Ortega; Juan Antonio Barberá; Bartolomé Andreo (J. Comput. Sci., 2025)