Automation
Intelligent Home Automation System
Research project developing a smart home platform with adaptive lighting, behavioral pattern recognition, and web interface.
Project Overview
Research project that developed and implemented in a scale model of a comprehensive smart home automation platform combining IoT devices, machine learning, and web technologies. The experimental system featured adaptive lighting control, behavioral pattern recognition, and a user-friendly web interface, demonstrating the practical implementation of modern home automation concepts through a functional prototype.
Technical Implementation
- Web Application Architecture: Engineered a responsive web interface using Node.js and Express for device control and monitoring. Frontend utilized vanilla JavaScript with Material-UI components, providing real-time updates via MQTT.
- Database and Analytics: Implemented MongoDB for storing user preferences, history, and patterns. Utilized data analytics for predictive automation and personalized adjustments.
- Intelligent Control Systems: Developed adaptive lighting control (color temp, intensity) based on time, ambient light, and learned preferences. Incorporated ML models trained on user behavior for routine automation.
Key Features
- Predictive Automation: ML system analyzing user patterns.
- Adaptive Lighting: Dynamic light control.
- Real-time Monitoring: Dashboard for system status/analytics.
- Mobile Integration: Responsive design.
Research Outcomes and Achievements
- Successfully implemented and validated predictive automation concepts via scale model.
- Created a modular system architecture for future expansion.
- Demonstrated practical application of IoT, ML, and web tech in home automation.
