Nov 2024 – Jan 2025 · Android & IoT development
SmartLit — Voice-Controlled Multi-Room Lighting System
Voice-controlled IoT lighting system for smart homes. Android app with speech-to-text, LIFX API integration, multi-room control. University project at Stockholm University.
- Java
- Kotlin
- Android Studio
- LIFX API
- RecognizerIntent API
- Wi-Fi communication protocols
Last updated
Source: github.com/kimonsodu/voice-controlled-lighting
Context
University project at Stockholm University, Nov 2024 – Jan 2025. Individual build demonstrating user-centered IoT design for smart home automation.
Goal — provide hands-free control of WiFi-enabled lights via voice commands through a mobile app. Users can turn lights on/off, adjust brightness, apply mood lighting presets, and control multiple rooms from a single interface.
Features
- Voice control — native Android speech-to-text recognition for natural language commands
- Brightness adjustment — fine-grained control via slider UI
- Mood presets — predefined lighting profiles (energize, relax, focus, etc.)
- Multi-room management — organize and control lights across different rooms
- Live feedback — real-time bulb status and control response
Architecture
- Android frontend — Java + Kotlin with native RecognizerIntent for speech input, intuitive UI for brightness and profile selection
- Wi-Fi communication — direct protocol integration with LIFX smart bulbs over local network
- LIFX API — HTTP-based bulb control for state management and color/brightness commands
- Credential management — environment-based token handling (not hardcoded in repo)
Configuration
Sensitive credentials excluded from repository:
LIFX_TOKEN=your-lifx-api-token
LIFX_LIGHT_ID=your-light-id
Set via .env file or environment variables before running locally.
Stack
Android: Java, Kotlin, Android Studio, RecognizerIntent API. Hardware: Android smartphones, LIFX Wi-Fi-enabled smart bulbs. Integration: LIFX HTTP API, Wi-Fi protocols.
Takeaways
Voice-first UX changes interaction design — speech commands require clear affordances and confidence feedback. Real-time bulb response creates immediate feedback loops that matter more than the feature list on paper. Wi-Fi reliability becomes the limiting factor at scale.