Smart thermostat
In 2011, Nest Labs developed the Nest Learning Thermostat. The Nest Thermostat attempted to reduce home energy consumption by addressing the problems with programmable thermostats through the use of better technology. This new technology included the implementation of sensors, algorithms, machine learning, and cloud computing. These technologies learn the behaviors and preferences of the occupants, and adjust the temperature up or down to make the occupant comfortable when they are home and to save energy when they are away. Additionally, the Nest Thermostat connects to the home Wi-Fi. This allows users to change the temperature, adjust the schedule, and check energy usage from a smartphone or laptop. All of these features were part of Nest's goal to create an easy to use thermostat that saves users energy and money.
Smart thermostat
One study attempted to address this issue by adding more sensors throughout the house. Instead of using just one sensor in the thermostat, this team experimented with placing motion sensors and door sensors throughout the house to gain better understanding of the occupant's sleeping and occupancy patterns. These sensors communicated with each other and used an algorithm to quickly determine whether the occupants were active, sleeping, or away. The system used historical data to estimate when occupants would be returning and would begin “preheating” the home before they arrived. Additionally, the system would drift further from the set point when it was certain that no one was home. The study compared a standard ("reactive") smart thermostat and the multiple sensor system to a manual thermostat. The study concluded that a reactive smart thermostat with just on sensor saves, on average, 6.8% of energy consumption, while the multiple sensor system saved an average of 28% of energy consumption. This study again shows that, on average, smart thermostats achieve their goal of saving energy. It also shows that smart thermostats are not as well developed as they could be, and the addition of more sensors could result in better performance and energy savings.