[2603.19583] Skilled AI Agents for Embedded and IoT Systems Development

[2603.19583] Skilled AI Agents for Embedded and IoT Systems Development

arXiv - AI 3 min read

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Abstract page for arXiv paper 2603.19583: Skilled AI Agents for Embedded and IoT Systems Development

Computer Science > Software Engineering arXiv:2603.19583 (cs) [Submitted on 20 Mar 2026] Title:Skilled AI Agents for Embedded and IoT Systems Development Authors:Yiming Li, Yuhan Cheng, Mingchen Ma, Yihang Zou, Ningyuan Yang, Wei Cheng, Hai "Helen" Li, Yiran Chen, Tingjun Chen View a PDF of the paper titled Skilled AI Agents for Embedded and IoT Systems Development, by Yiming Li and 8 other authors View PDF HTML (experimental) Abstract:Large language models (LLMs) and agentic systems have shown promise for automated software development, but applying them to hardware-in-the-loop (HIL) embedded and Internet-of-Things (IoT) systems remains challenging due to the tight coupling between software logic and physical hardware behavior. Code that compiles successfully may still fail when deployed on real devices because of timing constraints, peripheral initialization requirements, or hardware-specific behaviors. To address this challenge, we introduce a skills-based agentic framework for HIL embedded development together with IoT-SkillsBench, a benchmark designed to systematically evaluate AI agents in real embedded programming environments. IoT-SkillsBench spans three representative embedded platforms, 23 peripherals, and 42 tasks across three difficulty levels, where each task is evaluated under three agent configurations (no-skills, LLM-generated skills, and human-expert skills) and validated through real hardware execution. Across 378 hardware validated experiments, we show t...

Originally published on March 23, 2026. Curated by AI News.

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