How do we make the “Smart Home” Smart?

How do we make the "Smart Home" Smart?

Without blinking, we today tend to call a lot of products and concepts smart. The light bulb that can be controlled through an app is smart, the dish washer that notifies you when it’s done is smart and the door lock that you can open through Bluetooth is also smart. But what’s so smart about them? We might find new ways of going about our daily lives which might be smart, but the products and their features are not smart, just connected. They provide accessibility (hopefully), but no intelligence.
Of course there are some exceptions that, at least to some extent, can be called smart. Soil sensors that tell us how to take care of our plants, robot vacuums that plans their cleaning efficiently and security systems using algorithms to determine who entered the door. But these are scarce and limited to specific tasks.

Then there are the smart home assistant like Alexa and Google Home that can be considered to have a certain level of artificial intelligence. But it’s usually for the functionality that is not related to the home, like answering questions and predicting when you want to go to work. In the home they are not much more than appealing remote controls.

How do we turn the Connected Home into the Smart Home?

So if we can agree on that today when we talk about the smart home, we’re actually referring to the connected home, how do we then make it into the real smart home?

Let’s first look at a few concrete examples of what could constitute a smart functionality in your home.

    • -Having the lights dim, music stop and tv starting to play the next episode of your current favorite tv series when you enter the living room after putting the kids to bed.
    • -Being notified that a service has been scheduled for your heating system as vibration data from the pump is showing a decline in performance.
    • -In preparation of you going to work, the car heater started 15 minutes ago and your smart speaker notifies you of a traffic situation on your normal route while the indoor AC lowers the temperature for the day.

All of these things require a combination of AI, interconnected devices and a lot of sensor data. They all “almost” exist today, but it will take surprisingly long before we can make use of the smart home as it’s sold in futuristic movies.

And here are a couple of reasons for that:

  • Lack of Integration - Predictions about your behavior in your home requires the correct data from several different devices. It’s not enough that your Philips Hue smart bulbs can be controlled by your Google Home. All the gathered data needs to be collected into one service with the necessary machine learning algorithms. This will first happen when everything is either standardized or there is a business case to provide this service. And hopefully that business case doesn’t revolve around selling your behavioral predictions to other companies.
  • The danger of inconvenient predictions - The only true prediction is that predictions will never be 100% true. While it might be acceptable that lights turn on in the living room when you didn’t intend to go there, or getting traffic information to work on your day off, it would probably not be acceptable having your coffee machine making morning coffee the day you wanted tea or unlocking the front door the time you just drove past your house. We can only dare predict things about people's behavior as long as a failure in the prediction is at the most causing a minor inconvenience. If a failure leads to a real inconvenience or distrust in the product, it will never be accepted by most consumers.
  • Lack of consumer value - The Smart Home market is still one of the markets that requires the highest focus on consumer value to progress past the enthusiasts into the mainstream market, but is instead doing the opposite. Products from major brands are still being connected because they can with little or no perceived real value for the consumer. And as long as companies doesn’t understand the importance of identifying the real value for consumers, we will never get into the much more complex predictive features of the smart home.
So what should we do?

Making the smart home intelligent in the same way that it’s portrayed in movies will unfortunately take time. It requires broader acceptance of smart home devices, more sensors, standardization and continued improvements with machine learning.

But in the meantime, there are still things you can do as an IoT solution provider to bring the smart home a few steps closer.

  • Focus on consumer value - never forget to always put consumer value first. A product with an advanced algorithm will still be perceived as dumb if it solves the wrong problem or no problem at all.
  • Understand advanced analytics - while machine learning & advanced analytics is definitely not for every product or use case, it’s important to understand its possibilities and potential on a high level. You don't have to know how to implement it, but you should be able to spot the opportunity when there is one.
  • Predictive maintenance - don’t forget the possibility of predictive maintenance. While this is a huge area within Industrial IoT it hasn’t found its way into consumer products yet. I have a connected dishwasher, but I’m pretty sure that it won’t tell me before it fails and it won’t help me find a local service technician. This is an opportunity that is available today for businesses to create products perceived as more intelligent and helpful.
  • Integrate and open products - While not making them intelligent in itself, ensuring products and data are open for integrations will allow consumers to link them with other devices making the overall solution, if not intelligent, at least “smarter”.

While the real intelligent home might still be far away, let's do what we can today to make it at least feel smarter. Make sure there is real value for the consumer and that the products are perceived as helpful. Don't connect a product for the sake of connecting it, do it because you believe you can solve a real problem for the consumer. Take you time to challenge your use cases and test them on real consumers.

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NFC: Used especially for wireless cash payments.




