Autonomy Elements

Marty CA big 1Every automation system requires 3 elements: sensors, controllers and effectors (or actuators).. An autonomous house requires that these elements be able to meet the needs of both the occupants and the structure without needing a person to make changes happen. This picture is Marty with an adapted ultrasonic distance sensor, taken from a video of an appearance on Computer America. 

There is, alas, no single approach to organizing our explanation of the overall automation set-up without confusing things. So, since one won't do, we'll use two. We can start here with a practical explanation of how we addressed the broad-strokes problems, then dive a little deeper into each of them in their own sections.

Sensors

Sharpn IR proximity sensorSomewhere between figuring out what we want to know and what we need to know comes the question, how are we going to know it? That gets us into the specific things we may need to measure (temperature, proximity, range, humidity, air pressure, door status, vehicle detection, vehicle identification, gas detection, smoke detection, ambient light, wind speed, soil moisture and so on) and a determination of the best ways to measure them. It brings us into secondary interpretations of primary sensors; for example, range detection may also help us determine speed and direction. It also allows us to make pragmatic choices; for example, with a garage that's 28 feet deep, neither the IR nor ultrasonic range sensors we want to use has enough range to reliably sense whether the garage door is open or whether there's a car in the garage space; only Lidar can work.

Happily, we solved a major, potentially complicated challenge by inventing a ceiling awareness pod (CAP) that we can install everywhere, a Bluetooth Beacon system for detecting and identifying cars with running engines and several other tricky little solutions.

For more about how we deal with sensors, see:

Some sensor data also comes from devices used for other purposes; for example, the surveillance cameras that ring the house can signal the presence of objects within their fields of view by monitoring the extent of pixel-shifting within an otherwise still image.

Our Products section has information about products we use in every part of this project, including information about specific sensors (as well as controllers and effectors).

Controllers

NRaspberry Pi 3 Model_Bo part of this design exercise has been as frustrating as the search for controllers and how to approach them. The home automation category includes hundreds of products but no one protocol there can handle all of the sensor and effector needs of the house project. Most products are of the wall measles variety, meaning visible little white lumps all over the place. Most require battery babysitting.  In many cases, their control languages are unsophisticated, unable to deal with conditions any better nuanced than if-then constructs. Some of them require connections to external servers in order to work. And most of them are too ornery to talk to each other. The Raspberry Pi shown here is part of the solution.

Patchwork quiltStitching patches together became a mandate. You may be aware that some vendors use the not-inappropriate term fabric when referring to their sensing and control systems for commercial and some residential automation, but today's overall challenge is that there are many such patches of fabric that remain detached from one another. If we distribute the processing, so that different kinds of controllers can each do what they're best at doing, the optimum approach may be make the sensor and effector end points and mid-points both more intelligent and better able to coordinate; this is the nature of a hierarchical system. A practical approach to weaving the patches of fabric into a metaphorical quilt can readily happen by using Raspberry Pi elements to each gather, analyze and report a result from aggregations of assigned information. A level above, yet another, modestly powered Raspberry Pi can make and implement higher-level decisions and commands. Communications between fabric patches will often happen relatively slowly (to conserve power and bandwidth), but these mid-point controllers can get full Ethernet bandwidth. 

For more about how we deal with controllers, see:

Our ceiling awareness pods (the house will have 30 of these) each provide, among other things, an 8 by 8 array of analog temperature measurements; a typical Raspberry Pi task aggregates these 64 measurements in 30 places into a complete map of the house, analyzing it as occupancy information, displaying it as a high-resolution map, displaying it as a low-resolution image and analyzing the evenness of airflow in heating or cooling each room. This section addresses these and other deployment issues. 

Effectors

AIRcable FlasherAwareness, even with intelligence, can only result in automation when they control something that can effect changes in the real world; in the design of androids, that's called the manipulative imperative. In a house, effectors are how automation can turn lights or fans on or off, open or close a garage door or an electronic deadbolt, phone the fire department, push a display to a door panel, signal when you've pulled far enough into the garage and more.

The information you'll find here:

All of these devices require power, and we will provide specifics for each. A conduit-fed 4-wire DC power feed throughout the house provides stabilized (and battery-backup, surge-protected) 3,3, 5 and 12-Volt sources everywhere, and we hack into devices to hardwire them to our DC supplies so there is no battery babysitting required. Most devices are mounted and connected via standard electrical boxes installed in ceilings or, on occasion, walls.

There is ultra-automation here, a generation-after-next technology for home control, but with the automation picking up more of the work to handle on its own; it's not there to give people more work to do.

Our emphasis is autonomy, not audacity.

 

 

 

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