ERTIS Research Group
ERTIS focuses its research activity on improving the management, accessibility and integration of embedded devices in the context of the Internet of Things. ERTIS is part of the ITIS Software institute.
Research Areas
ERTIS focuses on several research lines that address the challenges of embedded and distributed systems in real-time and critical domains. Our work is organized into the following areas
Digital Twins and Open Platforms
Architectures for modeling, simulation, and monitoring of physical processes, applied to domains such as agriculture, energy, and infrastructures.
Streaming Deep and Distributed Neural Networks over the IoT/Edge/Fog/Cloud
ERTIS investigates how to integrate deep neural networks with messaging systems for deployment across IoT, Edge, Fog, and Cloud environments, exemplified by its Kafka-ML framework, which manages the entire AI model lifecycle through data streams.
IoT, Edge, and Fog Computing
Middleware and distributed architectures that enable efficient data processing across heterogeneous devices and networks.
Real-Time and Critical Systems
Methods and tools to ensure predictability, functional safety, and cybersecurity in systems where failures are not acceptable.
Publications and Projects
Explore our latest research projects and publications in embedded systems and IoT.
Active Projects
- EVOLVE: Electric Vehicles Point Location Optimisation via Vehicular Communications EVOLVE aims to exploit the scientific excellence and expertise of key academic and industrial players into a joint collaborative effort to design, …
- DiTaS: A framework for agnostic compositional and cognitive digital twin services The requirements for continuous analysis and prediction of the real-time behavior of assets and their possible future state have led to the emergence …
- TRIATHLON: TRIhAlomeTHanes controL thrOugh AI-based techNologies The main objective of TRIATHLON (TRIhAlomeTHanes controL thrOugh AI-based techNologies) is to facilitate the management of water supply networks. …
Latest Publications
- Distributed digital twins on the open-source OpenTwins framework Sergio Infante; Julia Robles; Cristian Martín; Bartolomé Rubio; Manuel Díaz
- Towards flexible data stream collaboration: Federated Learning in Kafka-ML Antonio Jesús Chaves; Cristian Martín; Manuel Díaz
- A Methodology for the Development of Soft Sensors with Kafka-ML Antonio Jesús Chaves; Cristian Martín; Luis Llopis Torres; Enrique Soler; Manuel Díaz; Rohit Sharma; Gwanggil Jeon; Yan Zhang
- Integrating FMI and ML/AI models on the open-source digital twin framework OpenTwins Sergio Infante; Cristian Martín; Julia Robles; Bartolomé Rubio; Manuel Díaz; Rafael González Perea; Pilar Montesinos; Emilio Camacho Poyato
Visits
Some of the distinguished researchers and collaborators who have visited us recently. We value these exchanges as opportunities to foster innovation and collaboration in embedded systems and IoT.
