BuildingIQ is at the forefront of applying artificial intelligence/machine learning/optimization algorithms to HVAC systems. Our patented Predictive Energy Optimization (PEO) is the crown jewel among all intelligent algorithms. I’d like to take this opportunity to demystify our approach a bit more. Essentially, the algorithm makes an intelligent decision at each point in time to conserve energy and maintain room comfort. Imagine this simple case — at each point in time, the algorithm can choose between three options:
The ability to choose between these three options allows us to optimize the HVAC system in the following ways:
In reality, PEO can choose to increase the room temperature a little or a lot. This is not an easy decision to make as it requires an automated understanding of the thermal properties of the building. We are continuously improving this decision process to allow PEO to make better choices at each timepoint, using some of the following parameters:
Rui (Ray) Xu is Data Scientist at BuildingIQ. During his career, he has encountered many challenges in the transfer of human knowledge into machines, the interpretation of results of algorithms into human intuition, and the verification of evolving strategies. This experience has helped him to solve some of the most difficult and interesting problems in the industry. He describes himself as a bit quiet but also very energetic and assertive when there is a mathematical, simulated and/or experimental proof behind the scenes.