A Quantified House - My Talk to the Seattle Quantified Self Meetup
I delivered the following presentation to a meetup of the Quantified
Self group in Seattle tonight. The evening was a fascinating fusion of
medicine, technology and personal improvement. My talk fell between a
session on personal genome sequencing and another on measuring the
effects of coffee on blood pressure.
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.
Why automated learning is hard for a smart home. The perils of over-fitting, under-fitting and how the general unpredictable nature of life makes it hard to build a system that learns your behavior.
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.
Several years ago we did a major remodel. I did all of the finish electrical myself and supervised all of the rough-in electrical. I also put in all of the electrical system and water in our barn. I have opinions ...
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.