IoT Home Automation: Getting Started
Home automation has three major parts:
- Communication protocols
Each of these parts is equally important in building a truly smart home experience as per your need. Having the right hardware enables the ability to develop your IoT prototype iteratively and respond to technology pivots with ease.
Applications of Home Automation
Rebuilding consumer expectations, home automation has been projected to target wide array applications for the new digital consumer. Some of the areas where consumers can expect to see home automation led IoT-enabled connectivity are:
- Lighting control
- Lawn/Gardening management
- Smart Home Appliances
- Improved Home safety and security
- Home air quality and water quality monitoring
- Natural Language-based voice assistants
- Better Infotainment delivery
- AI-driven digital experiences
- Smart Switches
- Smart Locks
- Smart Energy Meters
The list is still not exhaustive and will evolve over the time to accommodate new IoT use cases.
Now that you are familiar with home automation applications, let’s have a detailed look at what components are involved in building a typical home automation prototype.
Home Automation Components
We have talked about them before, but let’s clearly separate our components that will finally help you build a realistic model of what major components are involved in building a smart home. The major components can be broken into:
- IoT sensors
- IoT gateways
- IoT protocols
- IoT firmware
- IoT cloud and databases
- IoT middleware (if required)
Home Automation Sensors
There are probably thousands of such sensors out there that can be a part of your custom solution, but it all depends on your needs analysis. We will break down IoT sensors for home automation by their sensing capabilities:
- Temperature sensors
- Lux sensors
- Water level sensors
- Air composition sensors
- Video cameras for surveillance
- Voice/Sound sensors
- Pressure sensors
- Humidity sensors
- Infrared sensors
- Vibrations sensors
- Ultrasonic sensors
Depending upon what you need, you may use one or many of these to build a truly smart home IoT product. Let’s have a look at some of the most commonly used home automation sensors.
The market is full of them, but the famous temperature sensors are DHT11/22, DS18B20, LM35, and MSP430 series from TI. The MSP430 series is more accurate than the rest, but at the same time, it is one of the most expensive for prototyping or initial product testing purposes. MSP430 tops all temperature sensors, as the precision and battery consumption is minimal with them.
The DHT11 has a very restricted temperature range and suffers from accuracy issues. DHT22, on the other hand, is a little bit more accurate but still, doesn’t make it as the preference.
The DS18B20, on the other hand, is more accurate, as opposed to digital temperature sensors like the DHT22 and 11. Dallas temperature sensors are analog and can be extremely accurate down to 0.5 degrees.
Take note that often, the temperatures that you directly sense from these sensors may not be very accurate, and you would occasionally see 1000 F or greater values no matter what you are doing.
There’s an entire logic that goes around building temperature sensors that we will address in another blog post.
Lux sensors measure the luminosity and can be used to trigger various functions range from cross-validating movements to turn the lights on if it becomes too dark. Some of the most popular light sensors are TSL2591 and BH1750.
Recent tests to include TSL2591 and BH1750 into low-powered IoT devices have found them to be working fairly well for most use cases.
Here’s a study done by Robert and Tomas that shows how these two compare against a spectrometer and a photodiode.
To get a good idea of whether these two sensors would meet your needs, we would suggest illuminance tests followed by normalizations of the data to observe deviations under various situations.
Water Level Sensors
While building your prototype, you may consider a solid state eTape liquid level sensor or, like others, just use an HC-SR04 ultrasonic sensor to measure the water level.
On the other hand, in other cases where those two don’t suffice, one has to utilize something that can deliver a much higher performance.
Float level sensors and other ICs like LM1830 offer a more precise measurement capability to IoT developers — although, they are substantially much more expensive than others.
Air Composition Sensors
There are a couple of specific sensors that are used by developers to measure specific components in the air:
- CO monitoring by MiCS-5525
- MQ-8 to measure Hydrogen gas levels
- MiCS-2714 to measure nitrogen oxide
- MQ135 to sense hazardous gas levels (NH3, NOx, Alcohol, Benzene, smoke, CO2
Most of these are sensors have a heating time, which also means that they require a certain time before they actually start delivering accurate values.
These sensors mainly rely on their surface to detect gas components. When they initially start sensing, there’s always something that’s there on their surface, some sort of deposition that requires some heating to go away.
Hence, after the surface gets heated enough, true values start to show up.
Video Cameras for Surveillance and Analytics
A range of webcams and cameras specific to hardware development kits are usually used in such scenarios. Hardware with USB ports offer to integrate camera modules to build functionality.
But utilizing USB ports is not very efficient, especially in the case of real-time video transfer or any kind of video processing.
Take the Raspberry Pi for example. It comes with a camera module (Pi cam) that connects using a flex connector directly to the board without using the USB port. This makes the Pi cam extremely efficient.
Sound detection plays a vital role in everything from monitoring babies to automatically turning lights on and off to automatically detecting your dog’s sound at the door and opening it up for your pet.
Some commonly used sensors for sound detection include the SEN-12462 and EasyVR Shield for rapid prototyping.
These sensors aren’t as good as industrial-grade sensors like those from 3DSignals, which can detect even ultra-low levels of noise and fine tune between various noise levels to build even machine break-up patterns.
These sensors bring the capability of sensing humidity/RH levels in the air to smart homes. The accuracy and sensing precision depends a lot on multiple factors, including the overall sensor design and placement.
But certain sensors like the DHT22 and 11, built for rapid prototyping, will always perform poorly when compared to high-quality sensors like HIH6100 and Dig RH.
While building a product to sense humidity levels, ensure that there’s no localized layer of humidity that is obscuring the actual results. Also, keep in mind that in certain small spaces, the humidity might be too high at one end as compared to the others.
When you look at free and open spaces where the air components can move much freely, the distribution around the sensor can be expected to be uniform and, subsequently, will require fewer corrective actions for the right calibration.