Nest Intelligent Thermostat

How the Nest Intelligent Thermostat Works?

Your heating, air conditioning and the ductwork that carries and recycles air between rooms make up the HVAC (heating, ventilation and air conditioning) system for your home. You control your home's HVAC through your thermostat. All you have to do is select your heating and cooling options and to set your desired indoor temperature. The thermostat does the rest, switching systems on and off based on the temperature it detects in the room.

The Nest Learning Thermostat goes beyond this simple temperature detection to make a real impact in your HVAC energy consumption. In this article, we'll see what Nest can do, how it does what it does, who's behind it and what challenges it faces in the HVAC industry.

To understand Nest's value, let's first look at what other thermostats do. All thermostats let you set a desired temperature and monitor the current temperature. You can also switch between heat and AC.

Many thermostats rely entirely on your settings. As a result, you might only adjust the thermostat when you feel uncomfortable. In addition, you may not think to adjust it before you leave home to save on energy while the house is empty.

The Nest Learning Thermostat aims to solve this problem. Nest actually programs itself by learning your behavior patterns and desired temperatures for certain days and times during the week, and then building a schedule for your HVAC.

Nest Features: Saving Energy

Nest features what the company calls Nest Sense technology to learns your day-to-day routine and maintains your HVAC schedule automatically, based on what it learns.

Nest creates an Auto-Away mode based on what it's learned. This sets a temperature for minimal HVAC activity when you're not in the building. You can also set an Away mode manually if you wish.

While it's actively heating or cooling, Nest displays an estimated time for the system to reach the desired temperature.

Nest displays a green leaf any time the thermostat is running at energy-saving settings. This can teach you to make energy-saving decisions. For example, if Nest has learned that you typically run your AC until the house is 74 degrees Fahrenheit (23.3 Celsius), you could turn up the temperature until you see the green leaf, perhaps at 76 degrees Fahrenheit (24.4 Celsius), to save energy. The leaf will always appear at cooling settings of 84 degrees Fahrenheit (28.9 Celsius) or higher and heating settings of 62 degrees Fahrenheit (16.7 Celsius) or lower.

1. Nest lets you know what activity (between Auto-Away, your own adjustments and the weather) resulted in the greatest energy savings throughout the day.
2. Nest uses WiFi to connect to your Nest account at nest.com. This feature allows you to monitor and adjust the Nest remotely from the Web site.
3. Nest supports a mobile app available for Apple iOS devices (iPod Touch, iPhone, and iPad) and Android devices. The app turns your mobile device into a remote control for your Nest.
4. You can add Nest to any number of thermostats in a multi-thermostat building. They will work alongside other thermostats, but note that each of Nest's energy-saving features only applies to the rooms in its sensor range and to the HVAC components it controls.
5. Your Nest account can manage up to 10 Nest devices, whether they're in the same building or at multiple locations.

Nest Technology: Nest Sense

The core technology behind Nest is a combination of its sensors, computer and algorithms. The company calls this Nest Sense. Part of Nest Sense's job is to gather data to use in its calculations. This data goes beyond just measuring the temperature in the room. In fact, Nest gathers data from the following sources:

1. Three temperature sensors, designed to get a more precise measurement than a single sensor
2. Motion and light sensors that detect activity in the room at a wide 150-degree angle
3. A WiFi connection to get weather data about your area from the Internet

Using data from these sources, Nest Sense creates a schedule for your HVAC.

Related Reading: Artificial Intelligence used in Intelligent Devices
Related Reading: How Neural Networks are used in Intelligent Devices?

Intelligent Homes with Artificial Intelligence

What are these Intelligent Homes?

Whether it's a fully integrated house filled with interactive devices or a single component within an environment, there are three main pieces to creating an intelligent reactive device. First, it has to be able to detect what is going on. We humans use our senses to gather information about the environment around us and the others who may be in it. Sensors do the same thing for electronics, though a sensor may have a narrower scope of stimuli it can detect.

The interactive environment must also have some sort of processing unit that interprets the data gathered by sensors. This is the brain of the interactive environment. It stores user profiles and matches them with preferences. When a sensor detects that a specific person has entered the environment, this processing unit determines the next course of action.

The final piece is some sort of actuator, switch or setting that the processing unit engages to change the environment to best suit the user's needs. This might be a thermostat setting, a sound system or even a haptic feedback system that alerts you to specific conditions.

An interactive environment could have a central processing unit through which all components operate. This would allow for a single point of operation. All the data gathered by sensors would pass through the processing unit, which would send out commands to adjust the environment as needed.

Another approach is to use multiple, independent systems within an environment. This means that you might have an intelligent thermostat and an intelligent sound system but the two aren't connected to each other. One potential advantage of this approach is that if one component's processing unit fails, the others should still work without a problem. Interactive environments may also use a combination of systems with some integrating with a central unit while others are independent.

Today's intelligent reactive devices learn from patterns. Let's look at a thermostat as an example. Let's say your ideal temperature is 70 degrees Fahrenheit (21 degrees Celsius). When you're home, that's what you want. But let's say you're away from your home during the day. You may not care if your home gets a little warmer or cooler than 70 degrees at that point. So you set the thermostat a little higher -- or lower, depending on the time of year -- than your normal comfort zone to save power. When you come back home, you reset the thermostat and wait for your house to get comfortable again.

Many modern thermostats have a programmable mode that lets you set temperatures for particular times during the day. You could program your thermostat to adjust to a different temperature after you leave and return to your preferences an hour or so before you get back. You'll still be saving energy, but you won't have to come home to a hot or cold house.

An intelligent reactive thermostat could learn these patterns by recording when you make adjustments to the temperature. If you make a pattern of adjusting the temperature - for example, if you like it toasty in the morning but cave-cold in the evening - the intelligent thermostat can keep a record of it and make these adjustments for you once it has figured out your preferences.

The Nest thermostat does just that. It also has a motion detector built in so that it can adjust these settings on the fly. Maybe you've got a day off - something a normal programmable thermostat would be unable to determine. The Nest could detect you as you move about the house and make sure to override its normal routine so that you remain comfortable.

The Nest also has a WiFi transmitter that allows it to check weather reports. This lets the system know if it will need to work harder to maintain the ideal temperature inside the house. This adds a second layer of artificial intelligence over pattern recognition - search and learning.

The thermostat is a comparatively simple application of an intelligent environment. For example, you might have a favorite chair you sit in. Sometimes you sit there when watching television. Other times you might be reading or listening to music. In a fully automated home, sensors might be able to determine when you sit in the chair. But what does the home do next?

In general, the way AI makes decisions involves sets of actions. When you watch television, those actions could include turning on the TV and any other home entertainment equipment you have. It may also involve closing the blinds to block outside light. You might like to watch movies in a dark room, so the house dims the lights inside as well.

But if you wanted to read a book, a dim room with a blaring television may not be the environment you had wished. Instead, you might want a nearby lamp to be on while you sit in a quiet room and read. In this case, the house would need to turn off any gadgets that make noise and turn the light on for you. But how does the house know which set of actions to follow?

It sounds like a simple problem -- after all, you know if you want to watch TV, read or listen to music. But the house has to learn. It might do this by observing your behavior over several days, looking for patterns and patterns within other patterns. Otherwise, it might turn on the lamp when you really wanted the television.

This is mainly a software problem. Programmers help AI become smarter by building in a feedback system so the program keeps track of how frequently it gets things right and wrong. It gradually builds a database keyed to your behaviors so that it can anticipate your needs based on past experience. It may still get things wrong once in a while.

Things get more complicated when there are multiple people living in one house- or working in the same building. The software for the intelligent environment will have to build databases for each person and tweak them over time. And then there's the question of prioritization - if two people have drastically different preferences, how does the intelligent house take that into consideration?

Related Reading: What Artificial Intelligence is all About?
Related Reading: How Neural Networks is used in Intelligent House?