EMBEDDED DEEP LEARNING FOR REAL-TIME INTELLIGENT ENVIRONMENTS

Intelligent environments play a crucial role in shaping the future of connected living spaces, healthcare systems, transportation networks, and pervasive monitoring solutions. With the rise of deep learning and AI, significant progress has been made in perception, decision-making, and multimodal sensing. However, deploying these models in real-world scenarios introduces new challenges, including efficiency, reliability, explainability, and operation under strict resource constraints.

The Workshop on Reliable and Efficient AI for Intelligent Environments aims to provide a forum for researchers, practitioners, and industry professionals working at the intersection of AI, edge computing, and embedded systems. The workshop seeks to bridge the gap between algorithmic innovation and practical deployment, encouraging collaboration across disciplines to ensure AI systems are not only accurate but also robust, transparent, and resource-aware.

We invite submissions on lightweight deep learning architectures, privacy-preserving and explainable AI, multimodal sensing strategies, and methods for real-time deployment in intelligent environments. The goal is to encourage discussion on advancing state-of-the-art solutions that enable efficient and trustworthy AI in domains such as smart homes, healthcare, transportation, and beyond.

This workshop will be held as a co-located event in the 22nd International Conference on Intelligent Environments (IE'26).