develops an Asynchronous Federated Learning framework to improve vehicle operation analytics for diverse fleets of commercial EVs, tackling scalability, connectivity, and efficiency. By combining edge computing and MLOps, it focuses on real-time energy forecasting, activity recognition, and anomaly detection while ensuring data privacy. The consortium includes Volvo Trucks, Swedish research institutes, and SMEs.
uses AI to optimize Volvo’s aftermarket services, boosting efficiency and part availability via predictive logistics.
transforms industrial data into actionable insights using AI, to optimize assets like trucks, pumps, and network equipment, collaborating with Swedish industry partners and research institutes.
Machine learning library tailored for data streams. Featuring a Python API tightly integrated with MOA (Stream Learners), PyTorch (Neural Networks), and scikit-learn (Machine Learning). CapyMOA provides a fast python interface to leverage the state-of-the-art algorithms in the field of data streams.
MOA is the most popular open source framework for data stream mining.
