Hugging Face Trending Papers

Trust in Edge-Enabled IoT Security: Features, Challenges and Research Directions

arXiv AI
Jul 7

Agentic IoT: Architectures, Applications, and Challenges Toward the Internet of Agents

arXiv:2607. 04219v1 Announce Type: new Abstract: The integration of AI into Internet of Things (AIoT) systems has gradually transformed them from passive data collection infrastructures into intelligent systems capable of anomaly detection, predictive maintenance, classification, forecasting, and optimization.

By R\"umeysa Hilal Sevin\c{c}, Bahaeddin T\"urko\u{g}lu, \.Ibrahim K\"ok
arXiv Machine Learning
3d ago

Towards a Cloud Fog Edge System for Smart Building

The article outlines a vision and recent progress toward a decentralized system that learns from real‑time building data, treating the building itself as a data center to enhance privacy and reduce dependence on external clouds. It introduces a lightweight, Kubernetes‑like orchestration framework for deploying AI services on low‑power microcontrollers, such as those in the Arduino ecosystem, enabling in‑situ learning on sensors. The work also presents experimental results for new online learning algorithms and proposes a cloud‑fog‑edge architecture using KOptim and FIWARE components.

By Christophe C\'erin, Mamadou Sow, Fr\'ed\'eric Andr\`es
Hugging Face Trending Papers
Jul 14

Internet of Agentic Things: Networked AI Agents for Closed-Loop IoT Orchestration

The paper introduces the Internet of Agentic Things (IoAT), an architectural framework that integrates agentic AI, IoT, cyber-physical systems, Physical AI, edge computing, and digital twins into a unified closed-loop orchestration framework. The proposed architecture consists of cloud, edge/fog, and physical IoT layers connected through autonomous AI agents that perceive, reason, coordinate, and actuate across distributed cyber-physical environments.

Hugging Face Trending Papers
Jul 16

EdgeFaaS: A Function-based Framework for Edge Computing

Edge computing brings unique challenges as the resources on the edge are highly diverse in capabilities and capacities, and highly distributed across many users and the physical world. Existing distributed computing frameworks cannot adequately handle this level of heterogeneity and distribution.