Home Innovation Moving The Connected Home Beyond “Because We Can”

Moving The Connected Home Beyond “Because We Can”

Many connected home devices at the moment are just gadgets (connected water purifier, anyone?). Built for fun, built as proof-of-concepts, built – with a shrug – ‘because we can’. However, even though the technology is still young, we should already be looking beyond ‘because we can’.


Did you know the smart home means that, pretty soon, your fridge will be able to order milk when you run out?

Question: do you care?

Many connected home devices at the moment are just gadgets (connected water purifier, anyone?). Built for fun, built as proof-of-concepts, built – with a shrug – “because we can”. However, even though the technology is still young, we should already be looking beyond “because we can”.

Let me ask you instead:

Would you care if you could be notified that your elderly relative didn’t put the kettle on in the morning as she does every day? Would you care if you could be told you’d left the oven on, or you’d left a pair of straighteners burning on the bed when you went to work?

If you manufactured fridges, would you care if the energy signature of your appliances could tell you about real-world performance and pre-alert you (and your customer) ahead of breakdowns or required repairs?

If you were an insurer, would you care about boosting home security and providing more accurate insurance quotes?

I would. The connected home needs to move from “because we can” to “because we care”.

Straight to the source

At first glance, this sounds like a lot of data points. And collecting data from every appliance in the home would be a chore.

But that’s not the smart way to do it. Instead, we should look for the common denominator: energy. That’s where we should look. Not by putting smart plugs in every socket either, that’s still hugely inefficient. Instead, we should go back to the meter, through which all of a home’s energy flows.

That data is the golden ticket – but only if used intelligently. Historically, technological and commercial limitations have meant that all we can do with this data is total it up and stick it in a utility bill – counting kilowatts like a steward counting football fans at a turnstile.

Now, new technology is making new things possible.

Some point to smart meters and software built on their data as a great leap forward. And it’s true that having data every 15 minutes (or even every few seconds) can help consumers and business make more informed decisions about their energy usage.

But how smart is that really?

The devil is in the detail, and detail comes from granularity. In this case, that means speed of data sampling. New things become possible when you talk about milliseconds, rather than seconds or minutes. And I really mean new, not just the same things at a faster speed. Now the stewards can describe everyone passing through the gate, not just count them.

This is because every electrical device has a unique electrical signature. If sampled at seconds or minutes, all of those signatures will be lumped together. It will just be noise. When you get down to milliseconds though, they are distinct. So much so that, even with multiple devices switched on at the same time, it’s possible to disaggregate the energy data for each and identify them by their pattern.

This means you can tell the toaster from the fridge; the TV from the radio; the washing machine from the dryer and know exactly when each one is on.

It would take months on end to sift through the data though, if it was simply fed back to a screen or spreadsheet for a user to interpret. The value lies in real-time insights, and for that, the only possible option is machine learning.

Machine learning is a nascent field where computer programmes are capable of ‘learning’ to do new tasks from datasets, rather than be explicitly programmed for every task they do. Advanced machine learning in the context of the smart home removes the need for a human to teach it every electrical signature, and within seconds the algorithms can distinguish the different devices in the home.

A smart home indeed

At this level, energy data isn’t even about energy anymore. Sure, you can save money more effectively by seeing, in real-time, your biggest energy-draining appliances. But that’s a limited benefit. This data transcends the energy conversation.
Think of safety and security. If an elderly person fails to switch on the kettle for their morning cuppa, relatives could be alerted to check whether something’s wrong. If a teenager forgets to switch off hair straighteners and leaves them on the bed (not a rare occurrence), an app could recognise that signature and send an alert. Or what about that oh-so common dread that you’ve left the oven on when you’re out? That could be banished forever.

Then there’s security: when you’re on holiday or out at work and the house is meant to be empty, you could be told if the lights are turned on.

Or – going back to the money saving – this data can tell you more than “use appliance X less” or “remember to turn off Y”? This type of data can even tell you when appliances are becoming inefficient or are about to break – letting you make informed decisions about new ones and avoid coming home to a freezer full of spoiled food and water damage. It could even work out which replacements are likely to give you the best ROI based on your usage habits. It’s smart home data that can make the rest of your home smarter – and cheaper.

But the data doesn’t just give insights on the appliances. It also tells you about the people that use them. Usage patterns could pave the way for powerful insights into our own lives. You could track your TV consumption or cooking habits. In the future, a complex understanding of a person’s behaviour pattern could even help show early warning signs of health issues such as dementia, or other behaviour changing illnesses.

That’s a smart home, all enabled by energy data while having very little to do with your electric bill. It’s a smart home that cares for its inhabitants.

A more connected world

The potential of that data doesn’t stop in the home though. Third parties can use that data to improve their products and services – improving their business while delivering excellent customer service.

For example, Whirlpool recently had to repair or replace an estimated 3.8 million tumble dryers which had an unfortunate habit of catching fire. This was due to excess fluff being exposed to the heating element – something which would have been reflected in its electric signature . If the manufacturer had access to this data, the problem might have been caught much earlier.

In the insurance industry, appliance usage behaviour could be used to validate insurance claims or product warranties. And consumer usage of appliances could be used to more accurately and competitively price home insurance policies.

Of course, as with all connected technology, data privacy and security will be key. If consumers can use it to monitor loved ones’ wellbeing or for intruders while they’re away, someone else could do the same with the data. Only technology that takes security threats seriously will be able to make a success of the smart home.

“Because we can” is no justification for introducing new technology into the home. Not beyond the gadget-geek crowd anyway. To make the smart home a reality, and to make it something people actually want in their houses, we have to make technology that works because we care. Because we care about the wellbeing of our families and property. Because we care about saving money. Because manufacturers, insurers and other third parties care about creating the best possible experience for their customers.

It’s still early days for the connected home market yet, but the technology already exists. Let’s make it actually smart.


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