Jul 2021
Machine learning at the service of energy efficiency in buildings
To put it simply, machine learning is a form of artificial intelligence that is capable of learning as it collects data. Through its calculations, it can solve complex problems and plan actions which it performs itself.
Defining machine learning
To put it simply, machine learning is a form of artificial intelligence that is capable of learning as it collects data. Through its calculations, it can solve complex problems and plan actions which it performs itself.
This technology isn't new, even though it is becoming more powerful each day. It started in the 1950s, and it is responsible, in particular, for the first battle won by a computer against a prominent chess player in 1997 ("Deep IBM's Blue ”against Garry Kasparov, during their second confrontation).
Today, AI is present in daily life via our phone's smart assistant. The latter learns from our activity and data; it suggests other things for us to do or it does them for us. The same goes for the websites we visit.
They use our data to their advantage, as algorithms suggest products and services that correspond to our tastes and needs. This can of course go much further. In the industrial sector, machine learning aims to predict consumption (of energy, of consumables, etc.) and to replenish stocks on a large scale.
Machine learning and energy use in tertiary-sector buildings
Heating, ventilation and air conditioning represent the largest energy expenditure for companies in the tertiary sector in particular. Today, thanks to smart meters and smart grids, precise information on energy consumption is available. This information can help to reduce expenditures. But that is not always enough for long-term energy savings, especially in professional buildings.
This is where machine learning and artificial intelligence come into play: not only do connected sensors and the IoT control consumption, they also possess a considerable amount of data about a given room (activity, passage, occupants' needs, etc.) which they can process.
They can therefore automatically change the temperature, the luminosity or the ventilation based on room presence. Machine learning is therefore a useful tool as it uses its own statistics to make sound energy decisions while also maintaining the comfort of users.
The cost of using artificial intelligence technology is very low compared to renovations. The latter can be necessary, but, since machine learning is based on active energy efficiency, it remains relevant before and after construction work.
Machine learning only requires the use of connected sensors and of a platform where the data is available and readable. Although, in the case of machine learning, actions are done automatically.
But the energy manager's analytical outlook remains essential. Fortunately, a machine can still be contradicted... and humans can find new useful information when they collect and sort through the data.
Machine learning: a smart building is a valued building
Thanks to machine learning and to its predictions, which are solely based on data and statistics, the building's energy performance increases.
This applies to the tertiary sector, to residential buildings and to homes for the elderly. Machine learning is also helpful when buildings are being constructed since it can anticipate problems and even determine architectural standards.
Machine learning can also help to secure risk areas so as to protect construction workers. These new characteristics are good news for the real estate market as a whole.
What are the capabilities of machine learning in terms of predictive maintenance?
In the industrial sector, machine learning is now an essential tool to know the state of installations and equipment. It provides information on how long machines can last, on the need for consumables, the stock of spare parts, and, most importantly, it can detect failures before they happen...
For that reason only, companies waste less money and can continue to deliver their orders on time while also safeguarding their employees' safety. But machine learning isn't a magic wand.
It answers to technologies developed by humans and it is a big step forward for the sector in terms of productivity. It is essential for the industry to face the competition at a time when it is challenged by new technologies such as 3D printing. Unexpectedly, machine learning, when paired with industrial expertise, is opening up new paths for factories.
Regardless of their size, tertiary buildings, industrial buildings, public organisations... any building that produces or consumes energy can benefit from machine learning. This technology has extraordinary capabilities, but one doesn't have to be a large factory or a big company to benefit from it. The automated savings it generates are applicable everywhere.
Picture by Charles Deluvio on Unsplash
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