EdgeAI project

Edge AI Technologies for Optimised Performance Embedded Processin

About the project

The EdgeAI project is a European initiative focused on developing next-generation edge artificial intelligence technologies for intelligent, energy-efficient, and trustworthy embedded processing systems.

The project combines AI, embedded systems, microelectronics, and edge computing to enable distributed intelligence across industrial and societal applications.

Supported by the European Union through the Chips Joint Undertaking, the project contributes to Europe’s digital and green transition by reducing dependence on centralized cloud processing and enabling secure, low-latency AI at the edge.

Goal

The goal of the EdgeAI project is to strengthen European leadership in intelligent edge processing technologies by developing scalable hardware and software platforms for edge AI applications.

The project addresses challenges related to energy efficiency, privacy, explainability, security, and real-time operation across multiple sectors including digital industry, mobility, energy, agri-food, and digital society.

Our contribution

Almende contributes to the EdgeAI project within the Digital Society value chain by developing embedded AI solutions for smart environments and distributed sensing systems.

The work focuses on privacy-preserving and energy-efficient edge intelligence for intelligent building management and adaptive indoor environments.

A central part of the contribution is the advancement of smart power outlet technology for home and office environments, enabling fully edge-based AI applications without reliance on centralized cloud processing.

The developed solutions combine embedded machine learning, distributed intelligence, and contextual sensing for applications such as occupancy detection, activity recognition, device interaction analysis, and smart environment automation.

The resulting technologies will be integrated into existing Crownstone products, establishing a foundation for more advanced distributed AI capabilities and scalable smart building solutions.

These innovations support energy efficiency, privacy, and autonomous environment management, while strengthening the Crownstone platform for broader B2B applications and future market expansion.

Results

The project is expected to deliver advanced edge AI architectures, embedded processing platforms, AI middleware, and demonstrators validated in real-world environments.

Almende’s contribution supports the development of intelligent and privacy-aware indoor sensing systems capable of improving energy efficiency, sustainability, occupant comfort, and operational optimization.

The broader project outcomes strengthen the European ecosystem for trustworthy and sustainable edge AI technologies.

Partners

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