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Intelligent Machines

A Robotic Home That Knows When You’re Hungover

A company is developing apartment buildings with sensors, automated appliances, and the ability to learn an owner’s habits.

Perhaps the home of the future will be filled with robots. Or maybe that home itself will be a robot.

That’s the vision some technologists have for the future of domestic living, and a startup called Brain of Things announced Thursday that it is developing what the company’s founder refers to as “robot homes” in three locations in California.

These apartments come with a stunning array of sensors and automated fixtures and appliances. They also have the ability to learn and adapt to residents’ habits and preferences to an almost creepy degree, thanks to computer servers that collect data and use it to build models of behavior using machine-learning algorithms.

“The house knows the context, whether [its occupants] were watching a movie or sleeping or whatever,” says Ashutosh Saxena, a research fellow at Stanford and founder of Brain of Things, which is based in Redwood City, California. “As they are walking around the house, our house follows how they are acting, and it can know a lot.”

The blinds in the apartment will automatically lift when you rise for work in the morning, and lower mechanically at the right time in the evening. If the apartment senses that you just got up for a glass of water in the night, it will light the way without blinding you. It can even learn to keep the blinds lowered for longer on Sunday morning if you got in late or had friends over for a party.

Some might question whether their home really needs to take on a life of its own, but there is an undeniable trend toward adding more intelligence, connectivity, and communication ability to home fixtures. The thermostats sold by Nest, now owned by Google, learn to recognize users’ heating preferences, and products from companies such as Smart Things make it possible to access existing devices over the Internet and program them to behave more intelligently.

Saxena’s academic research focuses on ways for robots to learn and share information (see “10 Breakthrough Technologies 2016: Robots That Teach Each Other”). He says that while a great deal of attention has been paid recently to automating cars, automating the home may be even more important. “People spend 5.5 percent of their lives in cars,” he says. “We spend 68.7 percent out time in our homes.”

The homes that Brain of Things is developing are fitted with around 20 motion sensors, and the lights, the appliances, the entertainment systems, the heating and air conditioning, and the plumbing are all connected and automated. There is even an automated monitoring and feeding system that will reveal what a pet is up to during the day.

A resident can operate things normally, using a switch, but it’s also possible to use voice commands or a smartphone app. Over time, the apartment will learn a person’s preference and try to preëmpt them, though its behavior can also be overridden using a regular control.

The technology helps with maintenance, Saxena says, by identifying problems much earlier. Anticipating privacy concerns, he adds that there are no sensors in the bedrooms, and the data collected by each apartment doesn’t leave the building.

A few people are already living in apartments developed by Brain of Things in collaboration with a property development firm in Santa Rosa, California. The technology, which adds about $125 to the monthly rent, costs the property owner about $30 per month to install and maintain. It isn’t yet possible to retrofit an apartment with the technology, but Saxena says that’s something the company may offer in the future.

“Home automation is only going to get more useful as more advanced sensing technologies come out of the laboratory and into the home,” says Kamin Whitehouse, an associate professor at the University of Virginia who is researching smart building technology.

However, Whitehouse suggests that the sensors Brain of Things is using are relatively simple. “Motion sensors don’t tell you a whole lot,” he says. “They don’t know if you’re in a room standing still or have left a room.”

Whitehouse is experimenting with using wearable devices, as well as sensors that identify people by their height or hair color, as ways to track behavior. “We’re finding we can get a lot more information out of a Fitbit-type thing,” he says.

Though he admits that people will have privacy worries, he says the benefits, especially for the elderly or those with disabilities, should outweigh them. “People will have that reaction,” he says. “But they aren’t the target; I think the target audience is people who really need it.”

Saxena argues that since people touch the light switches on average 100 times per day, everyone should recognize the benefits. “One day people will think it very stupid they had to get up to turn on the lights,” he says.

Hear more about machine learning from the experts at the EmTech Digital Conference, March 26-27, 2018 in San Francisco.

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