World's Smartest House (Home Automation) wins 1st and 3rd
My entry to the Microsoft .NET competition 'My Dot Net Story' came in
1st and 3rd. You can see the certificates
here.
The entry was a project I've been working on to automate our home. We
now use over 40% less electricity than we used to use and our gas usage
is also down substantially.
The graph at the right shows both electricity and gas consumption
declining steadily year on year as the system becomes smarter about
different ways to save energy. For example, it knows which rooms are
occupied and which are not and can shut the lights off in any zone
that's no longer in use. It knows when we are home or away and it
knows the difference between an evening out and a week long trip. Using
all of these inputs it can decide what to do.
I've been working on home automation for over 15 years and I'm close to achieving my goal which is a house that understands where everyone is at all times, can predict where you are going next and can control lighting, heating and other systems without you having to do or say anything. That's a true "smart home".
An overview of the many sensors I've experimented with for home automation including my favorite under-floor strain gauge, through all the usual PIR, beam and contact sensors to some more esoteric devices like an 8x8 thermal camera.
One way to reduce the volume of sensor data is to remove redundant points. In a system with timestamped data recorded on an irregular interval we can achieve this by removing co-linear points.
Home automation systems need to respond to events in the real world. Sometimes it's an analog value, sometimes it's binary, rarely is it clean and not susceptible to problems. Let's discuss some of the ways to convert these inputs into actions.
Another super useful function for handling sensor data and converting to probabilities is the logistic function 1/(1+e^-x). Using this you can easily map values onto a 0.0-1.0 probability range.
In a home automation system we often want to convert a measurement into a probability. The ATAN curve is one of my favorite curves for this as it's easy to map overything onto a 0.0-1.0 range.
An if-this-then-that style rules machine is insufficient for lighting control. This state machine accomplishes 90% of the correct behavior for a light that is controlled automatically and manually in a home automation system.
