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+# Question Decomposition
+
+## Original Question
+Assess solution_draft01.md for weak points, performance bottlenecks, security issues, and produce a revised solution draft.
+
+## Active Mode
+Mode B — Solution Assessment of draft01
+Rationale: solution_draft01.md exists in OUTPUT_DIR. Assessing and improving.
+
+## Problem Context Summary
+- Three-tier semantic detection (YOLOE-26 → Spatial Reasoning + CNN → VLM) on Jetson Orin Nano Super (8GB, 67 TOPS)
+- Two-level camera scan (wide sweep → detailed investigation) with ViewPro A40 gimbal
+- Integration with existing Cython+TRT YOLO detection service
+- YOLOE-26 zero-shot bootstrapping → custom YOLO26 fine-tuning transition
+- VLM (UAV-VL-R1) as separate process via Unix socket IPC
+- Winter-first seasonal rollout
+
+## Question Type
+**Problem Diagnosis** — root cause analysis of weak points
+Combined with **Decision Support** — weighing alternative solutions for identified issues
+
+## Research Subject Boundary Definition
+- **Population**: Edge AI semantic detection pipelines on Jetson-class hardware
+- **Geography**: Deployment in Eastern European winter conditions (Ukraine conflict)
+- **Timeframe**: 2025-2026 technology (YOLO26, YOLOE-26, VLMs, JetPack 6.2)
+- **Level**: Single Jetson Orin Nano Super device (8GB unified memory, 67 TOPS INT8)
+
+## Decomposed Sub-Questions
+
+### Memory & Resource Contention
+1. What is the actual GPU memory footprint of YOLOE-26s-seg TRT engine + existing YOLO TRT engine + MobileNetV3-Small TRT + UAV-VL-R1 INT8 running on 8GB unified memory?
+2. Can two TRT engines (existing YOLO + YOLOE-26) share the same GPU execution context, or do they need separate CUDA streams?
+3. Is sequential VLM scheduling (pause YOLO → run VLM → resume) viable without dropping detection frames?
+
+### YOLOE-26 Zero-Shot Accuracy
+4. How well do YOLOE text prompts perform on out-of-distribution domains (military concealment vs COCO/LVIS training data)?
+5. Are visual prompts (SAVPE) more reliable than text prompts for this domain? What are the reference image requirements?
+6. What fallback if YOLOE-26 zero-shot produces unacceptable false positive rates?
+
+### Path Tracing & Spatial Reasoning
+7. How robust is morphological skeletonization on noisy aerial segmentation masks (partial paths, broken segments)?
+8. What happens with dense path networks (villages, supply routes)? How to filter relevant paths?
+9. Is 128×128 ROI sufficient for endpoint classification, or does the CNN need more spatial context?
+
+### VLM Integration
+10. What is the actual inference latency of a 2B-parameter VLM (INT8) on Jetson Orin Nano Super?
+11. Is vLLM the right runtime for Jetson, or should we use TRT-LLM / llama.cpp / MLC-LLM?
+12. What is the memory overhead of keeping a VLM loaded but idle vs loading on-demand?
+
+### Gimbal Control & Scan Strategy
+13. Is PID control sufficient for path-following, or do we need a more sophisticated controller (Kalman filter, predictive)?
+14. What happens when the UAV itself is moving during Level 2 detailed scan? How to compensate?
+15. Is the POI queue strategy (20 max, 30s expiry) well-calibrated for typical mission profiles?
+
+### Training Data Strategy
+16. Is 1500 images/class realistic for military concealment data? What are actual annotation throughput estimates?
+17. Can synthetic data augmentation (cut-paste, style transfer) meaningfully boost concealment detection training?
+
+### Security
+18. What adversarial attack vectors exist against edge-deployed YOLO models?
+19. How to protect model weights and inference pipeline on a physical device that could be captured?
+20. What operational security measures are needed for the data pipeline (captured imagery, detection logs)?
+
+## Timeliness Sensitivity Assessment
+
+- **Research Topic**: Edge AI resource management, VLM deployment on Jetson, YOLOE accuracy assessment
+- **Sensitivity Level**: Critical
+- **Rationale**: Tools (vLLM, TRT-LLM, MLC-LLM for Jetson) are actively evolving. JetPack 6.2 is latest. YOLOE-26 is weeks old.
+- **Source Time Window**: 6 months (Sep 2025 — Mar 2026)
+- **Priority official sources**:
+  1. NVIDIA Jetson AI Lab (memory/performance benchmarks)
+  2. Ultralytics docs (YOLOE-26 accuracy, TRT export)
+  3. vLLM / TRT-LLM / MLC-LLM Jetson compatibility docs
+  4. TensorRT 10.x memory management documentation