So what is machine learning, and what role can it play in a home energy management system like carbonTRACK?
Machine learning is the process by which software makes decisions based on its own observations and insights; it is one important component in the broader field of artificial intelligence. Systems that use machine learning are more sophisticated than conventional programming, in which the software simply follows a set of inbuilt, static rules with no ability to review or improve its performance.
Software that is capable of machine learning can make conjectures, test different approaches and assess their outcomes without the direct intervention of a human intellect. Using these inferences, the system can make up new provisional rules for itself to follow – all while continuously monitoring whether these rules are helping it to achieve its prescribed goals. A machine learning system will get progressively better at calling the shots over time – even when conditions are not cast in pure black & white.
The first widespread application of machine learning was for spam / junk email filters. In the decade after the use of email became widespread and commonplace, spammers finding ways to send junk to inboxes around the world. Email service providers wanted to provide their users with a better experience by eliminating spam.
The first simplistic, static filters made their decisions based on the appearance or absence of spammy keywords in the email. These filters had a low success rate compared to modern ones, sometimes failing to block actual spam while other times erroneously marking bona fide messages as junk. Pre-programmed spam-filtering algorithms could simply not keep up with the spammers’ growing arsenal of tricks.
Rather than engaging in an arms race that would require larger and larger teams of programmers to keep ahead of spammers, the anti-spammers developed filters that could ‘think for themselves’, making decisions based on a range of feedback they received and data they acquired as they went along. These highly sophisticated filters could update themselves to keep up with new spamming tactics.
Machine learning – as a type of artificial intelligence – may sound futuristic, but you might be surprised by how common it is. In fact, odds are that it benefits you in some way in your day-to-day life. Here are just a few examples:
An energy management that incorporates machine learning will make decisions that deliver more benefits your home than a system that does not. carbonTRACK’s machine learning functionality is some of the most sophisticated in the home energy management space.
At any given moment, the carbonTRACK platform is working away, trying to decide on the most cost-effective way to use energy in your home without compromising comfort. The more devices in the home, the more variables there are to make decisions about. Add in factors like a solar PV system, a battery bank, time of use electricity billing and electricity spot market trading, and the decision making process can become staggeringly complex for an ordinary human with limited (or even a lot of) time on their hands.