A predictive maintenance model uses sensors and IoT technology to monitor the condition of equipment and predict when it will need repairs or replacements. This equipment may be anything from personal cars to large factory machines.
The machine learning programs used to run these models tend to take either the regression approach or the classification approach. Regression produces more accurate results but relies on more data; classification best predicts equipment failure within a set time period.
Smart building technology arms a building’s component systems with the ability to communicate with each other and with management. Security systems, plumbing, electricity, waste management, temperature control, and more work exchange data constantly in order to improve the comfort and safety of people living or working inside the buildings.
Smart building technology works for both residential and commercial buildings.