Making a Plan
The thermostat is a comparatively simple application of an intelligent environment. In my case, the system may have a command that resembles "if Jonathan is home, then set the thermostat to 70 degrees Fahrenheit." But not all reactions are simple if-then problems.
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?
The good news is that there are dozens of different universities, companies and research organizations working on creating an intelligent reactive environment. While it may be years before anyone creates a standardized approach, we'll likely see intelligent appliances and gadgets make their way into our homes in increasing numbers soon.