Over the past few months, previously obscure terms like viral droplets, aerosols and airborne transmission have become part of our everyday vocabulary. Yet even before Covid-19, the quality and safety of the air we breathe posed a serious public health challenge.
As we all recently learned, being stuck indoors with suspicious air isn’t all that great. But it’s not only coronavirus that has us reaching for our masks – other, more mundane forms of toxins such as nitrogen oxides and sulfur oxides travel through the air in the office and at home.
To combat this situation, buildings are equipped with filters and fresh-air systems that clean the air coming in. But they can’t take on all the gaseous pollutants and ultra-fine particles that waft in.
This is where Israeli startup Urecsys steps in. Founded in 2014, the company developed a solution that uses big-data analysis and machine learning to predict air pollution levels both inside buildings and in their surroundings.
This enables ventilation systems to draw in outdoor air only when pollution levels are low, ensuring that people breathe in the cleanest air possible.