An innovative cross-platform system that revolutionizes device display and audio management through intelligent environmental sensing, real-time adjustments, and blazing-fast performance.
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# Build & run Rust backend (optional - auto-detected)
./scripts/build_rust.sh release
./scripts/build_rust.sh python # Python bindings# Install dependencies
pip install opencv-python numpy numba sounddevice
# Run the system manually
python3 adaptive_brightness_volume.py
# Run performance benchmarks
python3 benchmark_numba.py# Install mathematically optimized cron scheduling
./install_crontab.sh
# Check controller status
./adaptive_controller_manager.sh status
# View real-time logs
tail -f /tmp/adaptive_controller.log
# Manual control (if needed)
./adaptive_controller_manager.sh start|stop|restart🌅 Sunrise/Sunset Optimization: The system uses intelligent sunrise/sunset scheduling with geographic awareness for optimal energy efficiency:
- ~90% energy savings vs continuous running - only activates during light transition periods!
- Dynamic activation windows - 30min before to 2h after each sunrise/sunset (automatically calculated for your location)
- Geographic intelligence - auto-detects coordinates or uses manual configuration
- Seasonal adaptation - windows automatically adjust as days get longer/shorter
- Optimized flash detection - 40-second wait then compares with saved state (>40% change threshold)
- Eliminates unnecessary activations outside natural light transition periods
- Fallback protection - reverts to time-based logic if sunrise/sunset calculation fails
✅ 🦀 Rewrote core engine in Rust with SIMD vectorization for 2-4x speedup over Numba JIT
✅ Engineered a self-learning controller utilizing computer vision and audio processing
✅ Implemented dual-backend architecture - Rust for max performance, Python+Numba fallback
✅ Developed predictive algorithms for seamless transitions with adaptive smoothing
✅ Created intelligent activity detection and power efficiency optimization
✅ Achieved real-time performance monitoring with built-in timing statistics
✅ Designed sunrise/sunset scheduling system with ~90% energy optimization and geographic intelligence
✅ Built intelligent process management with smart threshold detection and auto-recovery
✅ Implemented flash detection system to eliminate unnecessary activations and system noise
✅ Created pure Python astronomical calculator using NOAA algorithms for location-aware time windows
✅ Engineered seasonal adaptation system with dynamic time windows that adjust with changing daylight
✅ Engineered comprehensive resource cleanup eliminating browser lag and system performance issues
✅ Developed robust signal handling with proper SIGTERM/SIGINT cleanup for burst mode termination
✅ Implemented advanced memory management with Numba JIT cache clearing and multi-pass garbage collection
✅ Created intelligent thread management with timeout-based cleanup and queue resource management
✅ Ensured cross-platform compatibility with multiple fallback methods for Linux distributions
🔹 Key Features:
Intelligent Brightness Control: Real-time ambient light analysis using OpenCV Dynamic adjustment with predictive algorithms Smooth transitions preventing eye strain Auto-calibration based on usage patterns Smart Audio Management: Ambient noise level monitoring Dynamic volume adjustment Adaptive audio scaling Noise filtering and normalization ⚡ Performance Optimization:
- 🦀 Rust SIMD Engine: 8-wide vectorized computations for maximum throughput
- Zero-Copy Interop: PyO3 bindings with direct NumPy array access
- Lock-Free Channels: Crossbeam-based concurrent architecture
- Branchless Algorithms: Conditional-move optimized change detection
- Numba JIT Fallback: Pure Python backend with 10-100x speedup when Rust unavailable
- Multi-threaded processing for minimal system impact
- Adaptive polling intervals to reduce resource usage
🧹 Advanced Resource Management:
- Comprehensive Cleanup System: Eliminates browser lag and system performance degradation
- Signal Handling: Robust SIGTERM/SIGINT cleanup for proper burst mode termination
- Memory Management: Numba JIT cache clearing with multi-pass garbage collection
- Thread Management: Timeout-based cleanup with proper thread joining and queue cleanup
- OpenCV Resource Cleanup: Force release of all camera handles and window destruction
- Performance Data Cleanup: Automatic clearing of monitoring data and accumulated state
- Zero Resource Leaks: Complete cleanup on any termination scenario (normal, timeout, interrupt)
🌅 Sunrise/Sunset Intelligent Scheduling System:
- Geographic Time Windows: Only activates during 30min before to 2h after sunrise/sunset periods
- ~90% Energy Savings: Dramatic improvement vs continuous running (up from 81%!)
- NOAA Astronomical Calculations: Pure Python implementation for accurate sunrise/sunset times
- Location Auto-Detection: Automatically detects coordinates from timezone or manual config
- Seasonal Adaptation: Windows automatically adjust as days get longer/shorter throughout year
- Optimized Flash Detection: 40-second wait then compares with saved state values (>40% threshold)
- Eliminates Unnecessary Activations: Complete deactivation outside natural light transition periods
- Fallback Protection: Reverts to time-based logic if astronomical calculations fail
- Comprehensive Resource Cleanup: Automatic cleanup after each 8-minute burst mode
- Signal-Aware Termination: Proper cleanup on timeout, interruption, or normal exit
- System Resource Monitoring: CPU load and memory usage protection
- Health Monitoring: Automatic process recovery with minimal frequency
- KDE Plasma Integration: User session and display state detection
- Professional Logging: Automatic log rotation with minimal footprint
System Integration:
Hardware-agnostic implementation Native OS controls integration Robust error handling Seamless background operation
🔹 Technical Stack:
| Layer | Technology | Purpose |
|---|---|---|
| 🦀 Core Engine | Rust + SIMD | Ultra-fast computations |
| 🐍 Bindings | PyO3 + NumPy | Zero-copy Python interop |
| 📷 Vision | OpenCV | Ambient light detection |
| 🔊 Audio | cpal / SoundDevice | Noise level analysis |
| ⚡ Fallback | Numba JIT | Python-only performance |
| 🔄 Concurrency | Crossbeam / Threading | Lock-free parallelism |
# Rust benchmarks (Criterion)
./scripts/build_rust.sh bench
# Python/Numba benchmarks
python3 benchmark_numba.py| Function | Numba | Rust | Speedup |
|---|---|---|---|
compute_noise_level |
0.15ms | 0.03ms | 5x |
calculate_brightness |
0.08ms | 0.02ms | 4x |
brightness_mapping |
0.008ms | 0.002ms | 4x |
volume_mapping |
0.015ms | 0.003ms | 5x |
smooth_transition |
0.0005ms | 0.0001ms | 5x |
screen_analysis |
0.08ms | 0.02ms | 4x |
change_detection |
0.01ms | 0.002ms | 5x |
💡 Tip: System auto-detects and uses Rust backend when available, with seamless Python fallback.
🦀 Rust-powered performance - 2-4x faster than Numba JIT, 4x lower memory footprint
✨ Significantly improved user comfort and productivity through intelligent adaptation
🌅 ~90% energy savings through sunrise/sunset scheduling with geographic intelligence (improved from 81%!)
🗺️ Location-aware operation with automatic coordinate detection and seasonal adaptation
🤖 Autonomous operation with reliable saved state comparison and minimal system impact
🖥️ Enhanced display and audio experience with eliminated taskbar flickering and fan noise
💻 Professional system integration synchronized with natural light cycles
📱 Superior battery life optimization through precise light transition period targeting
🌞 Perfect timing synchronization with sunrise and sunset events for optimal UX
🔍 Intelligent activation filtering - only operates during meaningful light change periods
🧹 Zero system lag through comprehensive resource cleanup eliminating browser and performance degradation
🛡️ Robust termination handling with signal-aware cleanup preventing resource leaks on any exit scenario
🚀 Clean burst cycles with proper thread, memory, and camera resource management
📅 Seasonal intelligence with automatic daylight adjustment throughout the year
This project demonstrates expertise in computer vision, signal processing, multi-threaded programming, and system optimization, while delivering a practical solution for everyday computing needs.
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