Artificial Intelligence and Machine Learning in the Smart HomeDecember 18, 2016
Facebook founder Mark Zuckerberg started 2016 with a resolution. His plan for the year was to explore the newly available smart home technologies and implement them into his home, in a way that the system itself coordinates according to his personal behaviour and lifestyle. Zuckerberg explained, his goal is to build a simple AI that would run his home and help him with his work. “You can think of it kind of like Jarvis in Iron Man,” he clarified.
The intelligent home, embracing a variety of AI-related technologies, is actively manifesting into an everyday reality. And interestingly, not just for the billionaires. The recently concluded Consumer Electronics Show (CES) in Las Vegas showcased expo showrooms with a spectrum of smart home devices that covered almost everything from smart thermostats to vacuums, lights and speakers.
So What Does it Take to Live in an AI-powered Smart Home?
When it comes to AI-powered smart homes, there are two significant approaches that are customarily considered - the world model, and machine learning. In a world model, the system intelligence is usually applied through programming, whereas the other approach, machine learning, develops a framework that virtually resembles a human thought process, leading to the creation of environments competent enough to learn and update its own world models.
Ideally, a smart home would combine a wide variation of sensory interfaces, such as voice and facial recognition, context-based suggestion, or responsive notifications that decrease the volume of input required on the part of a homeowner. All these would essentially come in concert to develop a spontaneous system, simplifying and streamlining a user's’ decision-making processes in a speedily changing ecosystem.
Key Advantages of AI-Integrated Intelligent Homes
The inherent benefits of artificial intelligence and machine learning are multidimensional. An AI-based smart home, besides optimizing resources and heightening the productivity of a user, can also add to the safety, proving to be life-saving in extreme scenarios such as a fire outbreak. The AI, sensing a blaze, would promptly alert each member of the house, intelligently escorting them to a secure location using only the routes it thinks are safe for them to use. Adults are notified throughout the process so that they are aware of the fire, position of the occupants, as well as the evacuation activities that are underway.
“It isn’t a stretch to suggest that machine learning is likely to shake up how we approach a connected home,” says Wojtek Zajac, Technology Director at Andrew Lucas London. “We can foresee a number of platforms becoming available – either from established home technology manufacturers or from new entrants – that incorporate increasingly intelligent learning mechanisms. These may well be built on top of, or otherwise engage with, the type of home automation interface that we’re currently familiar with, as well as providing more intuitive control options such as speech and facial recognition,” he adds.
Holger Knoepke, vice president of connected home at Deutsche Telekom, told BBC in an interview, “50% to 80% of people say they’re interested in smart home services.” “They could end up paying €5 to €10 a month, which equates to more than €15 billion ($17 billion) a year in Western Europe by 2019.”