AI System for Smart Lighting Management Based on Sensor Data
Lighting accounts for 20–40% of energy consumption in commercial real estate. AI-controlled lighting reduces this without comfort loss: precise brightness management based on actual presence and natural light.
System Architecture
Sensor Layer:
- PIR/ultrasonic presence sensors (90–95% detection accuracy)
- Light sensors (lux) for daylight harvesting
- CO2 sensors for indirect occupancy assessment
- Optional: cameras with people counting
Edge ML: On DALI controller or local Raspberry Pi:
- Occupancy prediction: Random Forest on temporal patterns
- Daylight model: AutoRegressive on historical lux data + weather forecast
- Adaptive dimming: RL agent maintaining target illuminance 300–500 lux
Control Layer: DALI (Digital Addressable Lighting Interface) — standard lighting control protocol. Group and individual light control.
What the System Does
- Switches off lighting when no people for N minutes (adaptive timeout per zone)
- Dims brightness when sufficient daylight
- Pre-enables light before people arrive (via calendar/pattern)
- Emergency lighting when motion detected at night
Metrics
| Metric | Value |
|---|---|
| Energy savings | 30–50% |
| System payback period | 2–4 years |
| Occupancy detection accuracy | 92–96% |