Cross-Modal Knowledge Distillation for wildfire evacuation logistics networks under real-time policy constraints

Short summary

Technique for optimizing multi-modal AI models for real-time wildfire evacuation decisions using knowledge distillation. Teacher model processes satellite imagery, text alerts, and sensor data; student model distills this to run on edge devices while respecting dynamic policy constraints. Implementation uses PyTorch with CNN for images, Transformers for text, and MLPs for sensor fusion.

• •Cross-modal knowledge distillation transfers understanding from large multi-modal teacher to smaller student model
• •Student model optimized for edge devices (drones, mobile) with constraint-aware loss function for policy compliance
• •Architecture includes CNN for satellite imagery, Transformer for text alerts, MLP for sensor data, with fusion layer

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