The widespread integration of IoT sensing in intelligent campus environments creates a strong demand for behavior recognition systems that are both reliable in crowded, rapidly changing scenes and efficient enough for real-time deployment. However, conventional video-centric approaches often struggle to capture cross-m...
Hai Chuan Liu, X. Zhao, A. S. M. Khairuddin et al.· IEEE Internet of Things Jour...· 0 citations
This review examines AI-driven locomotion, including reinforcement learning, non-RL machine-learning methods, model-based approaches, and hybrid strategies, with attention to robustness, sim-to-real transfer, sensor use, computational requirements, and hardware validation, and summarizes AI-supported advanced behaviors...
Li-Kai Wu, C. Chow, W. Wong et al.· Frontiers in Neurorobotics· 0 citations
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