Energy-Harvesting AIoT: Toward Sustainable and Intelligent Edge Systems

Dear Colleagues,

The convergence of artificial intelligence and the Internet of Things (AIoT) has ushered in a new era of intelligent and autonomous sensing. However, the scalability and sustainability of such systems remain constrained by energy limitations. Energy-harvesting AIoT (EH-AIoT) technologies offer a promising solution by enabling self-powered, context-aware devices that learn and adapt to dynamic environments. Through the integration of renewable energy harvesting, edge intelligence, and distributed learning, EH-AIoT systems can operate reliably even under intermittent power conditions.

This Special Issue aims to bring together researchers and practitioners to explore recent advancements in energy-harvesting–driven AIoT design, optimization, and applications. Topics of interest include, but are not limited to, the following:

• Energy-adaptive and approximate learning algorithms;
• Federated and distributed edge intelligence under power constraints;
• Reinforcement-based energy prediction and scheduling;
• Hybrid communication protocols (LoRa, BLE, 6LoWPAN) for EH-AIoT;
• Hardware–software co-optimization for sustainable AI systems;
• Energy-efficient sensor data processing and embedded inference;
• Real-world deployments of self-powered AIoT platforms.

We welcome both original research and comprehensive reviews that advance the understanding and practical realization of sustainable and intelligent energy-harvesting IoT systems.

Prof. Dr. Dong Kun Noh
Dr. Ikjune Yoon
Guest Editors

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