As an increasing number of industries adapt artificial intelligence, building management is no exception. AI and machine learning capabilities in the HVAC industry are producing smarter and more eco-friendly buildings. These advancements in technology are capable of significantly reducing energy usage and inefficiencies in the system. Due to its seemingly endless applications and ability to drastically improve the human experience, machine learning is the inevitable future of HVAC and building management.
What Is Machine Learning?
Machine learning is an application of artificial intelligence that is capable of learning from immense amounts of data and feedback. Its ability to learn and adapt based on data allows machine learning to make the best possible decisions. The longer it operates, the more data it acquires and the smarter it gets.
However, how machine learning collects data is ultimately up to control engineers and operators. While some opt for supervised machine learning, others prefer the unsupervised machine learning system. Regardless, machine learning is capable of processing vast amounts of data at any given time. This allows it to generally make better informed decisions than humans when it comes to HVAC systems and building management.
5 Ways Machine Learning Is Changing The Future Of Building Management
Here are some current applications of machine learning that are changing the future of HVAC systems and building management for the better.
Forecast Optimum Levels
The incredible thing about machine learning is its tendency to learn from each of its interactions. This means it is continuously improving its predictions. In addition to using the historical data of the building, machine learning can also factor weather forecasts and past human behavior in its predictions. As a result, machine learning is able to determine the most efficient temperature level in a building at all times.
“Machine learning collects data and finds patterns in it that humans would likely miss,” explains Sharron Blaylock, a technical writer at Essay Help and Britstudent. “This improves the efficiency of these smart buildings.”
Detect Problems Immediately
In addition to its predictive analytics abilities, machine learning can immediately detect a potential issue in the HVAC system. While many problems in the past would often go unnoticed until the unit completely shuts down, machine learning is capable of detecting the slightest errors immediately and notify a manager or maintenance team.
This enables professionals in building management to fix the problem before the damage is too great and the system becomes impossible to repair. This can save a lot of money that would otherwise be spent on purchasing new units.
BrainBox AI is able to learn how to best heat and cool a building using countless predictions. The technology, which was inspired by self-driving cars, applies intelligence-driven technology to HVAC systems and enables buildings to become autonomous.
One of the best parts about BrainBox is that it can be used anywhere with a centralized HVAC system that supports open communication. While it takes a few weeks to adjust and function to its full capabilities, it’s extremely convenient to be able to simply plug the AI and watch it improve the existing HVAC and building management systems.
Reduce Energy Costs
One of the biggest allures of machine learning to building management is its potential for significant cost savings. By determining the most efficient temperature and learning to predict usage based on a variety of factors, machine learning can drastically reduce the amount of energy wasted. This results in lower energy bills for the building.
Moreover, the ability of machine learning to detect slight issues in the system ensures the HVAC unit is functioning as optimally as possible. This reduces the amount of energy wasted that would otherwise go undetected. “Smart buildings powered by machine learning is a highly cost-efficient investment in the building management industry,” according to George Strickland, a business blogger at Write My X and Australia2write. “It reduces energy costs while improving the experience of building occupants.”
Minimize Carbon Footprint
The wasteful heating and cooling of a building over time produces a lot of unnecessary carbon emissions. Buildings are responsible for 30% of annual greenhouse gas emissions. By optimizing temperatures and minimizing energy waste, smart buildings enjoy a smaller carbon footprint than their non-smart counterparts.
As the impact of global warming continues to take its toll on populations across the world, it’s more important than ever to implement sustainable solutions such as machine learning to building management.
Machine learning is revolutionizing HVAC systems and building management. This advancement in technology is just getting started, and will no doubt continue to transform buildings into smarter ones. Machine learning must be the future if our goal is towards sustainable and smarter living.