SPIRE client
SPIRE client provides multiple helper functions to allow communication with the SPIRE server and manipulation of ROS bagfiles and topics
AI in cloud, edge and infrastructure is a field where the exploitation of data is crucial. This section makes the point on some recent advances in the field by giving references on ongoing research projects.
SPIRE client provides multiple helper functions to allow communication with the SPIRE server and manipulation of ROS bagfiles and topics
In the energy landscape that DSOs find themselves in today, predicting demand and the generation capacity of the systems to which they distribute becomes essential. This is mainly due to the injection of renewable energy among the consumers of the network...
The dataset provides energy consumption readings from a specific device, identified by UUID. The data captures detailed information, including the exact timestamp of the reading, energy consumed, and voltage, among other parameters. All readings are taken...
The Load Forecast Model is distinguished by its precision in predicting energy load demands, owing to its integration of advanced machine learning algorithms. Its cloud-hosted nature ensures scalability and adaptability, catering to both centralized and e...
Apache StreamPipes is a self-service (Industrial) IoT toolbox to enable non-technical users to connect, analyze and explore IoT data streams. The Apache StreamPipes Python Client is a new library targeted at data scientists, which helps to easily interact...
A basic Hello World example, walking you through the basic concepts of building an AI Solutions for AI4Experiments. It is written in NodeJS with comments explaining the most important lines of code. It implements two different setups highlighting the k...
Discover one of the breakthrough achievements of the ESFA project, a pioneer project in the field of Artificial Intelligence applied to Climate Prediction. Leveraging Geoskop’s revolutionary AI algorithms, housed in a Docker image, we provide unprecedente...
Preprint publication of deliverables for the preparatory actions of the AI-on-demand platform have been successfully carried out in the Pre-PAI project, which will serve as a blueprint for the "Deployment of the AI-on-demand platform" of the Digital Europ...
The AI4CNC experiment is designed to develop a Federated Learning System Platform for CNC machines to estimate tool wear through AI models and secure data sharing. The main objective is to use data from TEKNOPAR's CNC machines and sensors to estimate tool...