We have extensive experience in designing and implementing software architectures based on microservices for edge devices or gateways. These architectures are responsible for acquiring, processing, and sending data to public or on-premise cloud platforms. The devices are remotely configurable, controllable, and upgradable from the cloud platform. Additionally, ww have experience in optimizing, integrating, and deploying artificial intelligence models in resource-constrained devices.
We create microservice architectures using containers to make the system more elastic when orchestrating services and computing across the edge-to-cloud continuum. We also efficiently manage edge devices with different frameworks. Additionally, we integrate services such as Multi-Access Edge Computing (MEC) offered by the 5G network.
Our investigation focuses on techniques to optimize ML/IA models for specific computational capabilities of each device, carrying out the integration, deployment and inference of such models at the edge. We also centre on the lifecycle of artificial intelligence models deployed on devices, operating in edge-cloud environments.
Our pioneering and high-level facilities offer the essential tools to carry out tests and validations of different technologies and thus address challenges such as sustainability, energy efficiency and cybersecurity.
Our research is focused on the evolution of IoT and edge devices that integrate artificial intelligence and are able to acquire, process and communicate efficiently with edge-cloud architectures.