Enterprise AI Analysis
Mikro-İHA ile Yangın Sınırı Takibi için Termal-RGB Füzyonu ve Minimum İletişim Gereksinimi
This study introduces a lightweight perimeter-tracking method designed for micro-UAV teams operating over wildfire environments under limited bandwidth conditions. Thermal image frames generate coarse hot-region masks through adaptive thresholding and morphological refinement, while RGB frames contribute edge cues and suppress texture-related false detections using gradient-based filtering. A rule-level merging strategy selects boundary candidates and simplifies them via the Ramer-Douglas-Peucker algorithm. The system incorporates periodic beacons and an inertial feedback loop that maintains trajectory stability in the presence of GPS degradation. The guidance loop targets sub-50 ms latency on embedded System-on-Chip (SoC) platforms by constraining per-frame pixel operations and precomputing gradient tables. Small-scale simulations demonstrate reductions in average path length and boundary jitter compared to a pure edge-tracking baseline, while maintaining environmental coverage measured through intersection-merge analysis. Battery consumption and computational utilization confirm the feasibility of achieving 10–15 m/s forward motion on standard micro platforms. This approach enables rapid deployment in the field, requiring robust sensing and minimal communications for emergency reconnaissance applications.
Executive Impact
This research presents a novel, lightweight thermal-RGB fusion method for micro-UAVs to track wildfire perimeters with minimal communication. The system achieves robust detection, simplifies boundary data using Ramer-Douglas-Peucker, and operates efficiently on embedded System-on-Chip (SoC) platforms with sub-50ms latency. This significantly enhances rapid deployment and effectiveness in emergency reconnaissance under challenging conditions.
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Latency Target
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Forward Speed
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Communication Rate
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50ms
Target Latency for Real-time Operation
The system is designed to operate with sub-50ms latency on embedded System-on-Chip (SoC) platforms, ensuring real-time response capability for wildfire tracking.
Enterprise Process Flow
Sense
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Thermal-mask
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Edge-extract
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Fuse
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Simplify
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Guide
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Communicate
| Feature | Thermal-RGB Fusion | Pure Edge-Tracking Baseline |
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| Boundary Noise Suppression |
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| Hotspot Localization |
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| Robustness to Smoke/Glare |
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| Path Length Reduction |
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| Boundary Jitter Reduction |
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| Computational Efficiency |
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Application in Degraded GPS Environments
The system incorporates periodic beacons and an inertial feedback loop to maintain trajectory stability even in the presence of GPS degradation. This allows for continued, reliable perimeter tracking where traditional GPS-dependent systems would fail, crucial for remote wildfire operations. Small-scale simulations confirmed improved average path length and reduced boundary jitter compared to pure edge-tracking baselines, all while maintaining environmental coverage.
Outcome: Enhanced operational resilience and accurate tracking under challenging communication and navigation conditions.
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Potential Annual Savings
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Implementation Roadmap
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Phase 1: Initial System Integration & Test
Integrate Thermal and RGB sensor data with basic processing on a micro-UAV platform. Conduct initial flight tests in controlled environments to validate sensor fusion and basic perimeter detection algorithms. Establish communication links and inertial feedback loops.
Phase 2: Algorithm Refinement & Simulation
Refine adaptive thresholding, morphological operations, and Ramer-Douglas-Peucker simplification. Optimize guidance logic for leader-follower dynamics. Conduct extensive simulations to evaluate performance under varying conditions (smoke, GPS degradation, packet loss).
Phase 3: Field Deployment & Optimization
Deploy the system in real-world wildfire simulation environments. Collect performance metrics on latency, battery consumption, and path accuracy. Iterate on algorithm parameters and hardware configurations for optimal real-time performance and robustness.
Phase 4: Scalable Team Operations
Develop and test multi-UAV coordination strategies for large-scale perimeter mapping. Implement robust leader handover protocols and advanced communication frameworks (e.g., FANETs). Prepare for full operational deployment in emergency reconnaissance scenarios.
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