An adaptive edge system with FSM-guided tiering, multi-model YOLO consensus, and diurnal sensor fusion improves standing water detection performance while using less energy and maintaining bounded latency than static baselines.
An edge computing-based solution for real-time leaf disease classification using thermal imaging
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Edge-Based Standing-Water Detection via FSM-Guided Tiering and Multi-Model Consensus
An adaptive edge system with FSM-guided tiering, multi-model YOLO consensus, and diurnal sensor fusion improves standing water detection performance while using less energy and maintaining bounded latency than static baselines.