The RCWL-0516 microwave doppler radio board is a very cheap sensor for home automation. It responds to even slight motion anywhere within a considerable range (~10m) and it works through walls and other obstacles. It's not really "doppler" but it does detect changes in the interference between a weak transmitted microwave signal and the returned signal.
The downside to these properties is that it's no longer telling you about occupancy in a single room and it's susceptible to random triggers for no apparent reason. I tried the various hacks to reduce the sensitivity but it still triggers occasionally when it should not.
Given these properties I was forced to come up with a new approach in my home automation system that can handle unreliable sensors like this and sensors that span multiple rooms. My probabilistic model solved both these problems. By assigning a low probability to the radar sensor type and by associating each radar sensor with a percentage coverage in multiple rooms I can incorporate the useful data it provides whilst ignoring the spurious triggers.
In effect the radar sensor can confirm that someone is still in a room and it can detect someone has moved to a room (after multiple triggers each one increasing the likelihood of a move), but it cannot on a single trigger determine that someone has entered a room, nor even which room is being triggered.
The sensors are cheap and worth including in your home automation plans. Some commercial sensors combine technology like this with PIR to provide greater false rejection for both sensors which seems like a smart approach.
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".
My year long Bluetooth project that won the $20,000 HCI and Microsoft competition during lockdown has continued to grow and now reliably tracks how many people are in the house and outside and can locate any device down to room level.
Digital Twin are an online representation of a real world object, a copy of its properties in the digital world and a way to send updated and commands to it. In effect I've been making them for years but now they have a trendy name.
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.
ESP32 provides a great platform for sensors around the house but by the time you've added a USB power brick, cable and enclosure it's quite messy. I wanted a device that I could just plug in with no exposed wires and no mounting needed so I designed one in OpenSCAD.
Bluetooth sensing for home automation is a great proxy for people counting as it can detect and locate each cellphone in the house. iBeacons attached to tools, cars and pets can provide a 'find my anything' feature too.
Having at least one light sensor is critical for any home automation system that controls lightng. Lights need to be turned on when it's dark not at specific times of day, especially here in Seattle when it can be dark and cloudy at any time of day.
Optical-beam sensors are reliable and can cover a long-distance such as across a garage or aisle-way. When they include multiple-beams they have good false-trigger rejection.
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.
