As electric vehicles, renewable energy, and connected devices continue to grow, so does the amount of data generated at the edge of the network. Processing this data efficiently is becoming essential for building faster, smarter, and more resilient energy systems.
At Indigma, we are proud about our initiative ARIEL (federAted oRchestration In Ev fLeets), an innovative project funded through Open Call 1 of the O-CEI Project. Within ARIEL, we are collaborating with leading industrial partners, including Austrian Post and AVL, to develop next-generation Edge AI technologies that support intelligent energy management for large-scale electric vehicle fleets. By combining distributed intelligence with real operational environments, the project demonstrates how Edge AI can address practical challenges in the transition towards sustainable mobility.
Moving Intelligence Closer to the Source
Modern energy systems no longer rely solely on centralized cloud computing. Charging stations, electric vehicles, photovoltaic installations, and IoT devices continuously generate valuable data that can be used to optimize operations.
ARIEL brings Artificial Intelligence directly to these edge devices.
Instead of sending everything to the cloud, AI models are deployed where the data is generated, allowing local devices to process information, learn from their environment, and contribute to a larger intelligent network. This results in lower latency, reduced bandwidth requirements, improved scalability, and greater resilience for distributed energy systems.
Building the Edge AI Infrastructure
During the latest development phase, Indigma successfully delivered the first integrated ARIEL prototype, combining cloud orchestration with intelligent edge computing. The platform is designed to support real-world fleet operations, enabling industrial stakeholders such as Austrian Post and AVL to leverage distributed AI capabilities for more efficient management of electric vehicle charging and energy resources.
At the heart of the platform is FedMaestro, Indigma’s federated AI orchestration platform, which coordinates machine learning tasks across multiple distributed devices. Through an intuitive web interface, operators can launch experiments, monitor edge devices, manage AI models, and supervise the complete learning process from a single dashboard.
On the edge, lightweight AI clients run directly on devices such as Raspberry Pi, demonstrating that advanced machine learning workloads can operate even on resource-constrained hardware. This brings AI closer to real-world deployments where computing resources are limited but rapid decision-making is essential.
AI for Intelligent Fleet and Energy Management
ARIEL demonstrates how Edge AI can support the operation of large electric vehicle fleets by enabling distributed intelligence across charging infrastructure and connected devices.
As part of the project, Indigma developed AI models for electric vehicle charging demand prediction and solar energy forecasting, providing valuable insights that can help optimize charging schedules, improve renewable energy utilization, and support more informed operational decisions.
Designed for Real-World Edge Environments
Unlike many AI solutions developed only for cloud environments, ARIEL has been designed from the beginning for heterogeneous edge infrastructures.
The platform supports distributed devices with different computational capabilities, intermittent connectivity, and varying availability. It incorporates asynchronous orchestration mechanisms that allow AI training to continue even when some devices are temporarily offline or respond at different speeds. This makes ARIEL particularly well suited for large-scale deployments involving thousands of distributed edge nodes.
Shaping the Future of Edge AI
At Indigma, we believe the future of Artificial Intelligence lies beyond the cloud. Intelligent edge computing will play a fundamental role in enabling sustainable mobility, smarter energy grids, and next-generation digital infrastructure.
Through ARIEL, we are helping build the technologies that make distributed AI practical, scalable, and ready for real-world deployment-bringing intelligence exactly where it is needed most: at the edge.
Project ARIEL is supported by the European Commission under Grant No 101189589 through the Horizon EU program for the project “Open Cloud-EdgeIoT Platform Uptake in Large Scale Pilots (O-CEI)”.