1. Adaptive Control of House Environment - Neural Network House Presented by Wenjie Zeng

2. The Main Idea – Why Adaptive Control ? Smart houses aren’t smart –Difficult to customize –Complex interface baffles inhabitants –Inhabitants just forget to start the “automation” Adaptive house –Based on inhabitants’ lifestyle –Self-configuration, learning through mistakes –Change itself when inhabitants’ lifestyle changes

3. The Main Achievements – Optimal Control What did this work accomplish? – Air and water temperature regulation – Lighting (e.g. sleeping, reading, watching TV) – Neural nodes communication and coordination What are the contributions? – A mechanism to anticipate inhabitants’ needs – Saving energy (water not fixed at a temperature) – Optimal Control Model : Cost = Discomfort + Energy

4. The Challenges – How to predict Is inhabitants’ life pattern sufficiently regular ? Butterfly effect – Wrong decision -> future state - > future decision -> … Inhabitants have to get through the learning process of the adaptive system Example : Occupancy Model

5. Pictures Actual Deployment

6. Innovation Real Smart - Minimum human interaction Self-configuration through time Optimal Control method – event-based decision making