Every evening, we walk into the house and stay on the first floor from 5-11pm. The upstairs are heating or cooling; I hate the waste of energy. At bedtime, my daughter likes it at 60F and I like it at 70F. Sometimes we compromise on both being uncomfortable; sometimes one of us opens the window: more waste. The 4 quadrillion BTUs wasted per year create a $50B market and demand a solution that saves energy, respects the end user’s budget and increases comfort. Current smart heating, ventilation, and air conditioning (HVAC) solutions rely on a single central thermostat to control the heating and cooling for the entire home. This mechanism has two adverse effects: (1) most, if not all, rooms in the home are heated and cooled independently of occupancy; and (2) rooms that are not located near the thermostat have a different temperature than the overall desired temperature, resulting in uneven comfort. HiberSense is designing, developing, and implementing a distributed, inexpensive, and self- learning thermostat system that collects temperature, motion, light, humidity, and sound data in each room, runs machine learning algorithms to decide when to open/close our wireless motorized registers and turn on/off HVAC equipment to maximize savings and comfort. Our competitors build wirelessly-controlled registers, have fewer sensors, have no prediction algorithms, and have no subscription/alert services. HiberSense is compatible with smart thermostats (e.g., NEST) that provide the HVAC system control and one extra set of sensors.