Toward a Modular Architecture for Embedded AI Agent Systems at the Edge
The paper discusses a modular architecture for embedded AI agent systems designed to operate within the constraints of edge computing environments. It introduces a tiered design that separates on-device agents from cloud-augmented agents, allowing for efficient processing and decision-making. The architecture also includes a governance layer to ensure safety and policy enforcement across distributed devices.
- ▪The rise of Large Language Models has enabled more complex AI capabilities.
- ▪Existing frameworks often do not accommodate the limitations of embedded microcontrollers.
- ▪The proposed architecture aims to balance real-time control with agentic intelligence.
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Computer Science > Artificial Intelligence arXiv:2606.02862 (cs) [Submitted on 1 Jun 2026] Title:Toward a Modular Architecture for Embedded AI Agent Systems at the Edge Authors:Marcus Rüb, Michael Gerhards View a PDF of the paper titled Toward a Modular Architecture for Embedded AI Agent Systems at the Edge, by Marcus R\"ub and 1 other authors View PDF HTML (experimental) Abstract:The rise of Large Language Models (LLMs) has enabled agentic AI capable of complex reasoning and tool use; however, deploying such autonomy in pervasive computing environments remains challenging due to the strict memory and energy constraints of embedded microcontrollers. Existing frameworks typically assume server-class resources or continuous connectivity, leaving a gap for deeply embedded systems.
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